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Dissertations / Theses on the topic 'Image reconstruction'
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1
Jubb, M. D. "Image reconstruction." Thesis, University of Bath, 1989. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.328818.
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Nasir, Haidawati Mohamad. "Super-resolution image reconstruction from low-resolution images." Thesis, University of Strathclyde, 2012. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=17814.
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The thesis addresses the problem of obtaining high-resolution image from a set of one or more low-resolution images. The thesis focused on three building blocks of super-resolution algorithms i.e., image registration for super-resolution, image fusion for super-resolution and super-resolution image reconstruction. These three parts are addressed separately and singular value decomposition-based fusion is introduced before performing interpolation or single-image super-resolution. An accurate image registration is crucial for super-resolution. An image registration approach for super-resolution based on a combination of Scale Invariant Feature Transform (SIFT), Belief Propagation (BP) and Random Sampling Consensus (RANSAC) is described to automatically register the low-resolution images. The results have shown effective for the removal of the mismatched features in the image. A novel SVD-based image fusion for super-resolution is developed for integrating the significant features from low-resolution images. The SVD-based image fusion is shown to enhance the super-resolution results. The implementation of a novel interpolation method based on a linear combination of the bicubic interpolation and their first-order derivates and the use of first-order difference equation to extract the features from the low-resolution images are described and shown to improve the method of single image super-resolution using sparse representation. The proposed method has shown to reduces the computational time and enhance the prior estimation of the high-resolution image as well as the final super-resolution results. The performance of the algorithms is evaluated using synthetic sequences and also on real sequences subjectively and objectively.
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施能強 and Nang-keung Sze. "Image reconstruction with multisensors." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2001. http://hub.hku.hk/bib/B31226711.
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Sze, Nang-keung. "Image reconstruction with multisensors /." Hong Kong : University of Hong Kong, 2001. http://sunzi.lib.hku.hk/hkuto/record.jsp?B23621552.
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Azzari, Pietro <1979>. "Reconstruction from image correspondences." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2009. http://amsdottorato.unibo.it/1259/1/Azzari_Pietro_Reconstruction_from_image_correspondences.pdf.
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A single picture provides a largely incomplete representation of the scene one is looking at. Usually it reproduces only a limited spatial portion of the scene according to the standpoint and the viewing angle, besides it contains only instantaneous information. Thus very little can be understood on the geometrical structure of the scene, the position and orientation of the observer with respect to it remaining also hard to guess.
When multiple views, taken from different positions in space and time, observe the same scene, then a much deeper knowledge is potentially achievable. Understanding inter-views relations enables construction of a collective representation by fusing the information contained in every single image.
Visual reconstruction methods confront with the formidable, and still unanswered, challenge of delivering a comprehensive representation of structure, motion and appearance of a scene from visual information. Multi-view visual reconstruction deals with the inference of relations among multiple views and the exploitation of revealed connections to attain the best possible representation.
This thesis investigates novel methods and applications in the field of visual reconstruction from multiple views. Three main threads of research have been pursued: dense geometric reconstruction, camera pose reconstruction, sparse geometric reconstruction of deformable surfaces.
Dense geometric reconstruction aims at delivering the appearance of a scene at every single point. The construction of a large panoramic image from a set of traditional pictures has been extensively studied in the context of image mosaicing techniques. An original algorithm for sequential registration suitable for real-time applications has been conceived. The integration of the algorithm into a visual surveillance system has lead to robust and efficient motion detection with Pan-Tilt-Zoom cameras. Moreover, an evaluation methodology for quantitatively assessing and comparing image mosaicing algorithms has been devised and made available to the community.
Camera pose reconstruction deals with the recovery of the camera trajectory across an image sequence. A novel mosaic-based pose reconstruction algorithm has been conceived that exploit image-mosaics and traditional pose estimation algorithms to deliver more accurate estimates. An innovative markerless vision-based human-machine interface has also been proposed, so as to allow a user to interact with a gaming applications by moving a hand held consumer grade camera in unstructured environments.
Finally, sparse geometric reconstruction refers to the computation of the coarse geometry of an object at few preset points. In this thesis, an innovative shape reconstruction algorithm for deformable objects has been designed. A cooperation with the Solar Impulse project allowed to deploy the algorithm in a very challenging real-world scenario, i.e. the accurate measurements of airplane wings deformations.
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Azzari, Pietro <1979>. "Reconstruction from image correspondences." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2009. http://amsdottorato.unibo.it/1259/.
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A single picture provides a largely incomplete representation of the scene one is looking at. Usually it reproduces only a limited spatial portion of the scene according to the standpoint and the viewing angle, besides it contains only instantaneous information. Thus very little can be understood on the geometrical structure of the scene, the position and orientation of the observer with respect to it remaining also hard to guess.
When multiple views, taken from different positions in space and time, observe the same scene, then a much deeper knowledge is potentially achievable. Understanding inter-views relations enables construction of a collective representation by fusing the information contained in every single image.
Visual reconstruction methods confront with the formidable, and still unanswered, challenge of delivering a comprehensive representation of structure, motion and appearance of a scene from visual information. Multi-view visual reconstruction deals with the inference of relations among multiple views and the exploitation of revealed connections to attain the best possible representation.
This thesis investigates novel methods and applications in the field of visual reconstruction from multiple views. Three main threads of research have been pursued: dense geometric reconstruction, camera pose reconstruction, sparse geometric reconstruction of deformable surfaces.
Dense geometric reconstruction aims at delivering the appearance of a scene at every single point. The construction of a large panoramic image from a set of traditional pictures has been extensively studied in the context of image mosaicing techniques. An original algorithm for sequential registration suitable for real-time applications has been conceived. The integration of the algorithm into a visual surveillance system has lead to robust and efficient motion detection with Pan-Tilt-Zoom cameras. Moreover, an evaluation methodology for quantitatively assessing and comparing image mosaicing algorithms has been devised and made available to the community.
Camera pose reconstruction deals with the recovery of the camera trajectory across an image sequence. A novel mosaic-based pose reconstruction algorithm has been conceived that exploit image-mosaics and traditional pose estimation algorithms to deliver more accurate estimates. An innovative markerless vision-based human-machine interface has also been proposed, so as to allow a user to interact with a gaming applications by moving a hand held consumer grade camera in unstructured environments.
Finally, sparse geometric reconstruction refers to the computation of the coarse geometry of an object at few preset points. In this thesis, an innovative shape reconstruction algorithm for deformable objects has been designed. A cooperation with the Solar Impulse project allowed to deploy the algorithm in a very challenging real-world scenario, i.e. the accurate measurements of airplane wings deformations.
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Zeng, Gang. "Surface reconstruction from images /." View abstract or full-text, 2006. http://library.ust.hk/cgi/db/thesis.pl?COMP%202006%20ZENG.
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Rhoden, Christopher A. "Linear optimization and image reconstruction." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1994. http://handle.dtic.mil/100.2/ADA283641.
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莫紹祥 and Siu-cheung Mok. "Parametric halftoning and image reconstruction." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1988. http://hub.hku.hk/bib/B31208800.
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Cui, Xuelin. "Joint CT-MRI Image Reconstruction." Diss., Virginia Tech, 2018. http://hdl.handle.net/10919/86177.
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Modern clinical diagnoses and treatments have been increasingly reliant on medical imaging
techniques. In return, medical images are required to provide more accurate and detailed
information than ever. Aside from the evolution of hardware and software, multimodal
imaging techniques offer a promising solution to produce higher quality images by fusing
medical images from different modalities. This strategy utilizes more structural and/or
functional image information, thereby allowing clinical results to be more comprehensive
and better interpreted.
Since their inception, multimodal imaging techniques have received a great deal of attention
for achieving enhanced imaging performance. In this work, a novel joint reconstruction
framework using sparse computed tomography (CT) and magnetic resonance imaging (MRI)
data is developed and evaluated. The method proposed in this study is part of the planned
joint CT-MRI system which assembles CT and MRI subsystems into a single entity. The
CT and MRI images are synchronously acquired and registered from the hybrid CT-MRI
platform. However, since their image data are highly undersampled, analytical methods, such
as filtered backprojection, are unable to generate images of sufficient quality. To overcome
this drawback, we resort to compressed sensing techniques, which employ sparse priors that
result from an application of L1-norm minimization.
To utilize multimodal information, a projection distance is introduced and is tuned to tailor
the texture and pattern of final images. Specifically CT and MRI images are alternately
reconstructed using the updated multimodal results that are calculated at the latest step
of the iterative optimization algorithm. This method exploits the structural similarities
shared by the CT and MRI images to achieve better reconstruction quality. The improved
performance of the proposed approach is demonstrated using a pair of undersampled CT-MRI
body images and a pair of undersampled CT-MRI head images. These images are
tested using joint reconstruction, analytical reconstruction, and independent reconstruction
without using multimodal imaging information. Results show that the proposed method
improves about 5dB in signal-to-noise ratio (SNR) and nearly 10% in structural similarity
measurements compared to independent reconstruction methods. It offers a similar quality
as fully sampled analytical reconstruction, yet requires as few as 25 projections for CT and
a 30% sampling rate for MRI. It is concluded that structural similarities and correlations
residing in images from different modalities are useful to mutually promote the quality of
image reconstruction.Ph. D.
Medical imaging techniques play a central role in modern clinical diagnoses and treatments. Consequently, there is a constant demand to increase the overall quality of medical images. Since their inception, multimodal imaging techniques have received a great deal of attention for achieving enhanced imaging performance. Multimodal imaging techniques can provide more detailed diagnostic information by fusing medical images from different imaging modalities, thereby allowing clinical results to be more comprehensive to improve clinical interpretation. A new form of multimodal imaging technique, which combines the imaging procedures of computed tomography (CT) and magnetic resonance imaging (MRI), is known as the “omnitomography.” Both computed tomography and magnetic resonance imaging are the most commonly used medical imaging techniques today and their intrinsic properties are complementary. For example, computed tomography performs well for bones whereas the magnetic resonance imaging excels at contrasting soft tissues. Therefore, a multimodal imaging system built upon the fusion of these two modalities can potentially bring much more information to improve clinical diagnoses. However, the planned omni-tomography systems face enormous challenges, such as the limited ability to perform image reconstruction due to mechanical and hardware restrictions that result in significant undersampling of the raw data. Image reconstruction is a procedure required by both computed tomography and magnetic resonance imaging to convert raw data into final images. A general condition required to produce a decent quality of an image is that the number of samples of raw data must be sufficient and abundant. Therefore, undersampling on the omni-tomography system can cause significant degradation of the image quality or artifacts after image reconstruction. To overcome this drawback, we resort to compressed sensing techniques, which exploit the sparsity of the medical images, to perform iterative based image reconstruction for both computed tomography and magnetic resonance imaging. The sparsity of the images is found by applying sparse transform such as discrete gradient transform or wavelet transform in the image domain. With the sparsity and undersampled raw data, an iterative algorithm can largely compensate for the data inadequacy problem and it can reconstruct the final images from the undersampled raw data with minimal loss of quality. In addition, a novel “projection distance” is created to perform a joint reconstruction which further promotes the quality of the reconstructed images. Specifically, the projection distance exploits the structural similarities shared between the image of computed tomography and magnetic resonance imaging such that the insufficiency of raw data caused by undersampling is further accounted for. The improved performance of the proposed approach is demonstrated using a pair of undersampled body images and a pair of undersampled head images, each of which consists of an image of computed tomography and its magnetic resonance imaging counterpart. These images are tested using the proposed joint reconstruction method in this work, the conventional reconstructions such as filtered backprojection and Fourier transform, and reconstruction strategy without using multimodal imaging information (independent reconstruction). The results from this work show that the proposed method addressed these challenges by significantly improving the image quality from highly undersampled raw data. In particular, it improves about 5dB in signal-to-noise ratio and nearly 10% in structural similarity measurements compared to other methods. It achieves similar image quality by using less than 5% of the X-ray dose for computed tomography and 30% sampling rate for magnetic resonance imaging. It is concluded that, by using compressed sensing techniques and exploiting structural similarities, the planned joint computed tomography and magnetic resonance imaging system can perform imaging outstanding tasks with highly undersampled raw data.
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Mok, Siu-cheung. "Parametric halftoning and image reconstruction /." [Hong Kong : University of Hong Kong], 1988. http://sunzi.lib.hku.hk/hkuto/record.jsp?B1243713X.
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McKean, Lindsay. "'Feeling like me again' : reconstructing women's self-image through breast reconstruction." Thesis, University of Edinburgh, 2008. http://hdl.handle.net/1842/24951.
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An examination of the relevant literature revealed a lack of theoretical conceptualisations of breast reconstruction’s role regarding women’s self-image. The present study aimed to explore this topic further and develop appropriate theory. A Grounded Theory methodology was employed to retrospectively explore the experiences of women who had undergone breast reconstruction, focusing upon the concept of self-image. Ten participants took part in the current study, recruited from breast cancer support groups. Data was collected by means of semi-structured interviews and analysed via the NVivo 8 computer package. The views of three breast cancer care staff were also canvassed via focus group in order to verify the findings and emerging theory. The current investigation generated a core category entitled ‘Feeling like me again’. This category emerged as a reflection of the participants’ belief that breast reconstruction surgery has helped them to restore a sense of normality in their lives and in how they see themselves. The core category comprised two principal categories, namely ‘Normal Appearance’ and ‘Normal Life’, and their subordinate themes. A further two main categories were generated, entitled ‘Moving On’ and ‘Image of Sick Person’. The categories were formulated into a Model of Breast Cancer, Breast Reconstruction and Self-Image. Implications of this model in relation to existing theory and clinical practice were considered. This study has highlighted that breast reconstruction’s role in relation to women’s self-image is subtle and wide-ranging.
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Dodgson, Neil Anthony. "Image resampling." Thesis, University of Cambridge, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.240148.
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Breckon, W. R. "Image reconstruction in Electrical Impedance Tomography." Thesis, Oxford Brookes University, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.292254.
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Tang, Mengxing. "Image reconstruction in electrical impedance mammography." Thesis, De Montfort University, 2003. http://hdl.handle.net/2086/6260.
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Breast cancer continues to be a leading cause of death in Western countries. One of the most important approaches to reduce this mortality is to detect the cancer as early as possible. Although current diagnostic imaging modalities are able to give useful information for diagnosis, development of new imaging technique is highly desirable in order to detect breast cancer in an earlier stage. This is the motive of the present study of Electrical Impedance Mammography (ElM), which applies Electrical Impedance Tomography (EIT) to image human breasts. The overall aim of the whole project is to develop impedance imaging techniques and system for early detection of breast cancer. The aim of the studies reported in this thesis is twofold, to investigate methods of improving EIT image quality and the feasibility of EIT in breast cancer detection. Focusing on these aims the following work is reported: 1) The study of three different image reconstruction algorithms is described. In this work the image reconstruction results are compared and the most appropriate algorithm was chosen for the subsequent study of breast imaging. 2) An investigation of two important factors in EIT image reconstruction, the number of electrodes (NOE) and the number of conductivity basis functions (NOCBF) whose effects on EIT images have yet been studied in detail so far, are described. In this work the image reconstruction is analysed with different combinations of NOE and NOCBF using Singular Value Decomposition (SVD) and spectrum expansion theory. Finally suggestions are given on which configuration could offer better image quality in breast imaging3) A comprehensive investigation is reported regarding compatibility of different types of prior information and its effect on an iterative image reconstruction algorithm, based on which a novel method is proposed to improve EIT image quality. This method selects compatible prior information by observing the convergence behaviour of an image reconstruction algorithm. The principle, implementation, and results are detailed. Results indicate the effectiveness of this method. 4) A two-dimensional breast imaging simulation system is introduced. In this work several breast models with different physiological and pathological conditions are made, based on clinical in vitro measurements and Cole-Cole model. Images with different current frequencies are reconstructed and analysed. Results indicate the potential of detecting and identifying breast abnormality by EIT. 5) A preliminary study on 3D EIT and 3D electrode placement has been conducted. The mathematic principle and implementation of 3D EIT are described, followed by a study on the sensitivity of boundary measurements to the conductivity changes in a cylindrical object with 2 different types of electrode placement. Suggestions are given on optimal electrode placement in EIT breast imaging. Finally suggestions are gIven for future work. These include a) investigating appropriate electrode placement for different applications and corresponding current & voltage patterns; b) incorporating more prior information into ElM image reconstruction; c) designing a more precise 3D breast forward model; and d) investigating appropriate regularization for image reconstruction
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Chen, Joe. "Image Reconstruction in Serial Femtosecond Nanocrystallography." Thesis, University of Canterbury. Electrical and Computer Engineering, 2015. http://hdl.handle.net/10092/10661.
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X-ray crystallography is a form of microscopy that allows the three-dimensional arrangement of atoms belonging to molecules within crystals to be determined. In this method, a crystal is illuminated with a beam of X-rays and the diffracted amplitudes resulting from the illumination are measured and computationally processed to enable the electron density of the unit molecule, or the unit cell, constituting the crystal to be calculated. The recent development of the X-ray free-electron laser (XFEL) provides new routes for determining molecular structures via its ability to generate intense but brief X-ray pulses. These new instruments enable diffraction measurements to be obtained from crystals that have a small number of unit cells, referred to as nanocrystals, and molecular structure determination via this technique is known as serial femtosecond nanocrystallography (SFX).
This thesis is concerned with the characterisation of diffraction data obtained from SFX experiments and the techniques for reconstructing the electron density of the molecule from such data. The noise characteristics of diffraction measurements from nanocrystals is developed. Methods for directly inverting nanocrystal diffraction to obtain the electron density of the molecule are analysed and an approach to ameliorate the effect of noise is proposed and evaluated by simulation. A model for diffraction by nanocrystals that include the effects of different unit cell arrangements and incomplete unit cells on the crystal surface is also developed and explored by simulation. The diffraction by finite crystals is shown to be equal to the incoherent average over a set of unit cells that contain different molecular arrangements related to the symmetry of the crystal at hand. The problem of image reconstruction under this circumstance is investigated. The more general problem of reconstructing multiple, unrelated, objects from their averaged diffraction is also explored and uniqueness properties along with reconstruction algorithms developed. The problem of reconstructing multiple, related, unit cells is studied and preliminary results are obtained. These results show that iterative phase retrieval algorithms can in principle be adapted to reconstruct the electron density of a crystalline specimen from the data obtained in SFX and the retrieval of phases from the diffracted intensity averaged over multiple objects is feasible.
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Morris, Andrew. "Image reconstruction in magnetic induction tomography." Thesis, Cardiff University, 2004. http://orca.cf.ac.uk/54543/.
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Magnetic induction tomography (MIT) is a medical imaging technique that uses magnetic fields to image the electrical properties of the human body. In this work, a numerical model has been described and used to simulate MIT systems. A reconstruction algorithm, based on the sensitivity matrix method, has been used to reconstruct images of the internal conductivity distributions of samples, from simulated and experimental measurements. Images of conductivity contrasts of the magnitude encountered in human body have been successfully reconstructed. An initial investigation has made into wave propagation delays in MIT.
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Chang, Ka Kit. "Human model reconstruction from image sequence /." View Abstract or Full-Text, 2003. http://library.ust.hk/cgi/db/thesis.pl?MECH%202003%20CHANG.
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Thesis (Ph. D.)--Hong Kong University of Science and Technology, 2003.Includes bibliographical references (leaves 124-134). Also available in electronic version. Access restricted to campus users.
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Hurn, Merrilee Ann. "Models and algorithms for image reconstruction." Thesis, University of Bath, 1992. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.317339.
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Juengling, Ralf. "Advances in Piecewise Smooth Image Reconstruction." PDXScholar, 2014. https://pdxscholar.library.pdx.edu/open_access_etds/1671.
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Advances and new insights into algorithms for piecewise smooth image reconstruction are presented. Such algorithms fit a piecewise smooth function to image data without prior knowledge of the number of regions or the location of region boundaries in the best fitting function. This is a difficult model selection problem since the number of parameters of possible solutions varies widely.
The approach followed in this work was proposed by Yvan Leclerc. It uses the Minimum Description Length principle to make the reconstruction problem well-posed: the best fitting function yields the shortest encoding of the image data. In order to derive a code length formula, the class of functions is restricted to piecewise polynomial. The resulting optimization problem may have many local minima, and a good initial approximation is required in order to find acceptable solutions. Good initial approximations may be generated at the cost of solving a sequence of related optimization problems, as prescribed by a continuation method.
Several problems with this approach are identified and addressed. First, success or failure of the continuation method is found to be sensitive to the choice of objective function parameters. Second, the optimization method used in prior work may fail to converge, and, third, it converges too slowly to be useful in many vision applications.
I address the first problem in three different ways. First, a revised continuation method is less sensitive to parameter choice. Second, I show how to move control over success or failure from the objective function parameters to the continuation method. Third, a new objective function is derived which includes one parameter instead of the two parameters used in prior work. Experimental results show that all measures improve robustness with respect to parameter choice.
In order to address the optimization-related problems I use a quasi-Newton line-search method. This method is guaranteed to converge and may converge at a faster rate than the relaxation method used in prior work. To realize a faster convergence rate, I introduce a new parameter whose role is to improve variable scaling and problem conditioning. Further runtime improvements result from using extrapolation in the continuation method. Experimental results show overall runtime improvements of an order of magnitude and more.
My reconstruction algorithm performs superior to the well-known Canny edge detector on the Berkeley boundary detection task. This is a novel result that demonstrates the merits of image reconstruction as a means for extracting information from an image.
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Menon, Daniele. "Color Image Reconstruction for Digital Cameras." Doctoral thesis, Università degli studi di Padova, 2009. http://hdl.handle.net/11577/3426401.
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Recently we observed a fast diffusion of digital cameras that are able to acquire images and videos directly in the digital format. This new acquisition technique allowed to explore new strategies to process, save and display images and videos.
Digital cameras require many operations to process the data acquired by the sensor. In this thesis I present an overview of the techniques used in practical realizations and proposed in the literature. Particular attention is paid to the algorithms that are more connected to the image processing area.
Among them, the process that is the most important for the quality of the resulting images and the most computational demanding is demosaicking. This consists in the reconstruction of the full color representation of an image from the data acquired by a sensor provided with a color filter array that in each pixel acquires a color component only instead of the three values that are necessary to represent a color image. The most common color filter array is called Bayer pattern, from the name of his inventor Bryce Bayer. In this thesis an overview of the demosaicking techniques presented in the literature is given and three new methods that allow to obtain good performances with a reduced computational cost are proposed. The first two are based on directional interpolations and are made adaptive to the image behavior through analysis of the edges and wavelet transformations. The last proposed technique, instead, is based on regularization methods, an useful tool to find a solution for an ill-conditioned inverse problem.
Since the sensor introduces a noisy component in the acquired data, an algorithm to perform demosaicking and denoising jointly is also analyzed. It exploits wavelet transformations.
Finally, a method to adaptively interpolate the image is presented, in order to increase the resolution and improve the visual quality of the details in the image. This technique is based on an analysis of the statistical local behavior of the image.Negli ultimi anni abbiamo assistito ad una rapida diffusione di fotocamere e telecamere in grado di acquisire immagini e video direttamente in formato digitale. Questo nuovo tipo di acquisizione ha dato la possibilità di esplorare nuove strategie per l'elaborazione, l'archiviazione e la visualizzazione delle immagini e dei video. Le fotocamere (e telecamere) digitali richiedono un elevato numero di operazioni per elaborare i dati acquisiti dal sensore. In questa tesi viene offerta una panoramica delle tecniche utilizzate nella pratica e di quelle presentate nella letteratura scientifica. In particolare, si è data particolare attenzione agli algoritmi maggiormente legati all'area dell'elaborazione dei segnali. Tra questi, il procedimento più importante per la qualità finale dell'immagine e più impegnativo per le risorse computazionali delle fotocamere è senza dubbio il demosaicking (traducibile con demosaicizzazione). Esso consiste nella ricostruzione della rappresentazione a colori dell'immagine a partire dai dati acquisiti con un color filter array che, in ogni pixel, preleva una sola componente di colore invece delle tre necessarie per la visualizzazione di un'immagine a colori. Un color filter array molto diffuso è il Bayer pattern, così chiamato dal nome del suo inventore Bryce Bayer. All'interno della tesi viene fornita un'ampia panoramica delle strategie proposte per il demosaicking nella letteratura scientifica e, inoltre, vengono presentati tre nuovi approcci in grado di fornire ottime prestazioni nonostante il loro ridotto costo computazionale. I primi due sono basati su interpolazioni direzionali e resi adattivi al contenuto dell'immagine attraverso opportune analisi del comportamento dei bordi e delle trasformazioni wavelet. Un'altra tecnica proposta, invece, è basata sui metodi di regolarizzazione, utili per trovare soluzioni in problemi matematicamente non invertibili. Dal momento che i sensori aggiungono una componente rumorosa ai dati acquisiti, viene analizzato anche un algoritmo che permette di effettuare congiuntamente demosaicking e denoising utilizzando delle trasformazioni wavelet. In conclusione, viene presentato un metodo per effettuare un'interpolazione adattiva dei dati in modo da aumentare la risoluzione e migliorare la visione dei dettagli. Tale tecnica si basa su un'analisi del comportamento statistico locale dell'immagine.
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Jayasooriya, Chandana K. K. Kwon Hyuck M. Jayaweera Sudharman K. "Zoom-based super-resolution image reconstruction from images with different orientations." Diss., A link to full text of this thesis in SOAR, 2006. http://soar.wichita.edu/dspace/handle/10057/649.
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Thesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical and Computer Engineering."December 2006." Title from PDF title page (viewed on Oct 31, 2007). Thesis advisers: Hyuck M. Kwon, Sudharman K. Jayaweera. Includes bibliographic references (leaves 48-50).
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Wear, Steven M. "Shift-invariant image reconstruction of speckle-degraded images using bispectrum estimation /." Online version of thesis, 1990. http://hdl.handle.net/1850/11219.
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Ganapathi, Annadurai Kartick. "3D Shape Reconstruction from Multiple Range Image Views." The University of Waikato, 2006. http://hdl.handle.net/10289/2267.
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Shape reconstruction of different three dimensional objects using multiple range images has evolved recently within the recent past. In this research shape reconstruction of a three dimensional object using multiple range image views is investigated. Range images were captured using the Waikato Range Imager. This range images camera is novel in that it uses heterodyne imaging and is capable of acquiring range images with precision less than a millimeter simultaneously over a full field. Multiple views of small objects were taken and the FastRBF was explored as a mean of registration and surface rendering. For comparison to the real range data, simulated range data under noise free condition were also generated and reconstructed with the FastRBF tool box. The registration and reconstruction of simple object was performed using different views with the FastRBF toolbox. Analysis of the registration process showed that the translation error produced due to distortion during registration of different views hinders the process of reconstructing a complete surface. While analyzing the shape reconstruction using the FastRBF tool it is also determined that a small change in accuracy values can affect the interpolation drastically. Results of reconstruction of a real 3D object from multiple views are shown.
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Yau, Chin-ko, and 游展高. "Super-resolution image restoration from multiple decimated, blurred and noisy images." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2004. http://hub.hku.hk/bib/B30292529.
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Stanford, Derek C. "Fast automatic unsupervised image segmentation and curve detection in spatial point patterns /." Thesis, Connect to this title online; UW restricted, 1999. http://hdl.handle.net/1773/8976.
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Le, Vesconte Helen. "Body image and body image investment in mastectomy and breast reconstruction." Thesis, University of Southampton, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.617817.
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Breast cancer is the most common cancer in women in the UK and both diagnosis and treatment can cause significant levels of distress and impaired quality of life. There arc many factors that relate to psychological distress in women coping with breast cancer including changes in body image. Appearance-related side effects, such as hair loss, are often reported as more severe than side-effects such as nausea and fatigue. A review of the literature explores the links between mainstream body image models and breast cancer. The impact of mastectomy on body image and mental health outcomes is discussed as well as the role of breast reconstruction, as this may help to alleviate women's body image difficulties and emotional distress following surgery. The need to understand the role of body image investment within theoretical models as well as for breast cancer patients facing mastectomy and immediate reconstruction is highlighted, especially in light of the inconsistencies found within the literature. The empirical paper investigates the psychosocial and body image outcomes of two groups of women: those undergoing mastectomy alone and those undergoing mastectomy with immediate breast reconstruction. It also examines whether investment in body image acts as a moderating variable between surgery type and subsequent psychological distress. Both groups reported deteriorations in their body image following surgery, though this did not always correspond with increased emotional distress. Women who reported a higher body image investment who underwent mastectomy alone had the poorest outcomes.
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Kinahan, Paul Eugene. "Analytic three dimensional image reconstruction from projections." Thesis, University of British Columbia, 1988. http://hdl.handle.net/2429/28492.
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This work presents an analytic three dimensional image reconstruction algorithm that was developed for a proposed volume-imaging PET scanner. The development of the algorithm was motivated by the scanner's ability to collect an order of magnitude more data than current PET systems and the lack of an efficient algorithm that could use the extra data.
The algorithm is based on an extension of the Recovery Operator of Orlov[68] and operates by convolution in object space. This method of operation sets it apart from other analytic direct image reconstruction algorithms that rely on Fourier transforms.
The algorithm is tested with ideal data and parameters that are appropriate to the new PET scanner. The results of the test show that the algorithm behaves as expected except for a 17% overshoot in the reconstructed value in one area. An explanation of this artifact is suggested, although not verified.
Finally, the efficacy of the algorithm is demonstrated by proving that it is functionally
equivalent to Fourier transform methods.Science, Faculty of
Physics and Astronomy, Department of
Graduate
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Wilson, Jack Thomas. "Image reconstruction of remotely-sensed planetary data." Thesis, Durham University, 2016. http://etheses.dur.ac.uk/11755/.
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Planetary data measured from orbiting spacecraft are defined on a sphere. Therefore, the geometry of the sphere must be taken into account in their analysis. In this thesis, I develop a Bayesian image reconstruction technique, based on pixon image reconstruction, but allowing the solution to tailor its fit to structure in the image. Unlike older implemen- tations this new method is capable of reconstructing data defined across the entire sphere without the need to partition the surface into approximately flat regions. The thorium line data from the Lunar Prospectors Gamma Ray Spectrometer are enhanced using pixon reconstruction. The enhancement shows that at the Compoton- Belkovich Volcanic Complex, thorium is distributed over a larger (40 km × 75 km) area than the (25 km × 35 km) high albedo region normally taken to define the feature. The thorium must have been deposited during the formation of the volcanic complex, because subsequent lateral transport mechanisms, such as small impacts, are shown to be unable to move sufficient material. The morphology of the feature is consistent with pyroclastic dispersal and we conclude that the present distribution of thorium was likely created by the explosive eruption of silicic magma. Application to Mars Odyssey Neutron Spectrometer epithermal data yields an improvement in resolution from 520 km to 290 km. This new high-resolution data is used to infer the global distribution of Water Equivalent Hydrogen (WEH) and reveals WEH-rich features near the equator at the Medusae Fossae Formation and the Tharsis Montes, which may indicate the presence of water ice. The data are also used to infer the polar abundance of CO2 throughout the Martian year, which is found to exhibit behaviour not predicted by the Martian general circulation models.
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Serackis, Artūras. "Image reconstruction technologies for protein spot parametrisation." Doctoral thesis, Lithuanian Academic Libraries Network (LABT), 2009. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2008~D_20090122_094213-80420.
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The problems of protein parametrisation in two-dimensional electrophoresis (2DE) gel image is analysed in this work. Analysis of the proteins gives possibility to observe the health state of living organisms. In proteomics two-dimensional electrophoresis is used for protein separation in the gel according to their isoelectric point and molecular mass. The resulting gel is scanned and analysed by automatic gel image analysis systems. Those systems are not able to deal with specific protein spot distortions found in the gel image. The over-saturated protein spots prevent proper segmentation of the 2DE gel images. The aim of the work is to investigate the possibility of image reconstruction applications for object parametrisation by creating new methods for protein spot parametrisation in 2DE gel images.
Three main tasks are resolved in this work: new mathematical models for parametrisation of saturated protein spots in 2DE gel images are proposed; new method for over-saturated protein spot search and reconstruction in 2DE gel images is proposed; new method for parametrisation of overlapped protein spots in 2DE gel images is proposed.
The thesis is divided into introduction, four chapters and generalisation. The review of image reconstruction techniques and current 2DE gel image analysis problems are presented in first chapter. In the second chapter – the new mathematical models for parametrisation of saturates protein spots are proposed and experimental investigation results... [to full text]Disertacijoje nagrinėjamos baltymų pėdsakų parametrizavimo dvimatės elektroforezės (2ME) gelių vaizduose problemos. Proteomikoje, analizuojant baltymus, tiriami gyvame organizme vykstantys pokyčiai. 2ME metu baltymai išskiriami pagal jų molekulines savybes. Deja 2ME gelių vaizdų automatinei analizei skirtose programose pritaikytos technologijos netinka iškraipytiems baltymų pėdsakams (dėl baltymų įsisotinimo, persisotinimo ar susiliejimo) aptikti ir parametrizuoti. Pagrindinis disertacijos tikslas – ištirti galimybę taikyti vaizdo rekonstravimo technologijas trimačiams objektams parametrizuoti, sukuriant ir ištiriant baltymų pėdsakų 2ME gelių vaizduose parametrizavimo metodus. Disertacijoje sprendžiami trys pagrindiniai uždaviniai: naujų baltymų pėdsakų matematinių modelių, tinkamų įsisotinusiems baltymų pėdsakams parametrizuoti, kūrimas; baltymų persisotinimų paieškos ir rekonstravimo metodo kūrimas ir susiliejusių baltymų pėdsakų parametrizavimo metodo kūrimas. Disertaciją sudaro įvadas, keturi skyriai ir rezultatų apibendrinimas. Įvadiniame skyriuje nagrinėjamas problemos aktualumas, iškeliamos hipotezės, formuluojamas darbo tikslas bei uždaviniai, mokslinis darbo naujumas, darbo praktinė reikšmė ir disertacijos struktūra. Pirmajame skyriuje apžvelgtos parametrizavimui taikomos vaizdo rekonstravimo technologijos. Skyriuje apžvelgtos vaizdo rekonstravimo technologijos, taikomos objektui parametrizuoti, kai naudojami keli, skirtingu kampu, gauti objekto vaizdai, taikomos... [toliau žr. visą tekstą]
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Polydorides, Nicholas. "Image reconstruction algorithms for soft-field tomography." Thesis, University of Manchester, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.488242.
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Zhang, Xin, and 张鑫. "Sectional image reconstruction in optical scanning holography." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2010. http://hub.hku.hk/bib/B4476487X.
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Pardoe, Andrew Charles. "Neural network image reconstruction for nondestructive testing." Thesis, University of Warwick, 1996. http://wrap.warwick.ac.uk/44616/.
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Conventional image reconstruction of advanced composite materials using ultrasound tomography is computationally expensive, slow and unreliable. A neural network system is proposed which would permit the inspection of large composite structures, increasingly important for the aerospace industry. It uses a tomographic arrangement, whereby a number of ultrasonic transducers are positioned along the edges of a square, referred to as the sensor array. Two configurations of the sensor array are utilized. The first contains 16 transducers, 4 of which act as receivers of ultrasound, and the second contains 40 transducers, 8 of which act as receivers. The sensor array has required the development of instrumentation to generate and receive ultrasonic signals, multiplex the transmitting transducers and to store the numerous waveforms generated for each tomographic scan. The first implementation of the instrumentation required manual operation, however, to increase the amount of data available, the second implementation was automated.
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Chandra, Sunil. "Texture image reconstruction from irregularly sampled data." Thesis, University of Surrey, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.431093.
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Sun, Benjamin K. (Benjamin Kao=Shing). "Ultrasonic reflection tomography : elliptical path image reconstruction." Thesis, Massachusetts Institute of Technology, 1997. http://hdl.handle.net/1721.1/43421.
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Giovagnoli, Debora. "Image reconstruction for three-gamma PET imaging." Thesis, Ecole nationale supérieure Mines-Télécom Atlantique Bretagne Pays de la Loire, 2020. http://www.theses.fr/2020IMTA0219.
Full textAbstract:
Dans cette thèse nous présentons l’imagerie trois gammas, où le système d’acquisition repose sur un émetteur bêta+ et gamma. La justification de l’imagerie 3-gamma est que les informations du détection du troisième gamma peuvent aider à fournir une meilleure localisation du point d’annihilation, permettant ainsi une meilleure qualité d’image et moins de dose délivrée au patient. Nous vous présentons le systéme 3-gamma XEMIS2, développé à Subatech, Nantes, qui est un détecteur basé sur Liquid Xenon, adapté à l’imagerie3-gamma grâce à son stopping power, ses caractéristiques de scintillation et sa géométrie continue. Le principe de la reconstruction d’image 3-gamma est basé sur l’intersection d’une LOR, obtenue à partir des photons de coïncidence, avec un cône Compton, déterminé par le troisième gamma. L’idée est de trouver l’intersection du cône et de la LOR et de l’utiliser pour localiser la position d’annihilation la plus probable sur la ligne, comme pour la différence en temps d’arrivé en TOF-PET. Nous présentons une étude de simulation GATE de deux phantoms (NEMA et Digimouse) pour évaluer les améliorations de la reconstruction d’image 3-gamma par rapport à la TEP conventionnelle, et nous étudions aussi la correction du range du positon, qui est important pour notre émetteur Sc44In this thesis we present three-gamma imaging, where the acquisition system relies on a beta+ and gamma emitter. The rationale of 3-gamma imaging is that the third gamma detection information may help to provide better localization of the annihilation point, thus enabling higher image quality and fewer dose delivered to the patient. We present the 3-gamma system, theXEMIS2, developed at Subatech, Nantes, that is a LiquidXenon detector suitable for 3-gamma imaging due to its stopping power, its scintillation characteristics and its continuous geometry. The principle of 3-gamma image reconstruction is based on the intersection of a LOR, obtained from the coincidence photons, with a Compton cone, determined by the third gamma. The idea is to find the LOR\cone intersection and use it to locate the most probable annihilation position on the line,as for the time difference in TOF-PET. We present a complete GATE simulation study of two phantoms (similar-NEMA and Digimouse), to assess the improvements of 3-gamma image reconstruction over conventional PET and we study the positron range correction, which is important for our beta+gamma emitter, Sc44
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Evans, Joshua. "Statistical image reconstruction for quantitative computed tomography." VCU Scholars Compass, 2011. http://scholarscompass.vcu.edu/etd/2557.
Full textAbstract:
Statistical iterative reconstruction (SIR) algorithms for x-ray computed tomography (CT) have the potential to reconstruct images with less noise and systematic error than the conventional filtered backprojection (FBP) algorithm. More accurate reconstruction algorithms are important for reducing imaging dose and for a wide range of quantitative CT applications. The work presented herein investigates some potential advantages of one such statistically motivated algorithm called Alternating Minimization (AM). A simulation study is used to compare the tradeoff between noise and resolution in images reconstructed with the AM and FBP algorithms. The AM algorithm is employed with an edge-preserving penalty function, which is shown to result in images with contrast-dependent resolution. The AM algorithm always reconstructed images with less image noise than the FBP algorithm. Compared to previous studies in the literature, this is the first work to clearly illustrate that the reported noise advantage when using edge-preserving penalty functions can be highly dependent on the contrast of the object used for quantifying resolution. A polyenergetic version of the AM algorithm, which incorporates knowledge of the scanner’s x-ray spectrum, is then commissioned from data acquired on a commercially available CT scanner. Homogeneous cylinders are used to assess the absolute accuracy of the polyenergetic AM algorithm and to compare systematic errors to conventional FBP reconstruction. Methods to estimate the x-ray spectrum, model the bowtie filter and measure scattered radiation are outlined which support AM reconstruction to within 0.5% of the expected ground truth. The polyenergetic AM algorithm reconstructs the cylinders with less systematic error than FBP, in terms of better image uniformity and less object-size dependence. Finally, the accuracy of a post-processing dual-energy CT (pDECT) method to non-invasively measure a material’s photon cross-section information is investigated. Data is acquired on a commercial scanner for materials of known composition. Since the pDECT method has been shown to be highly sensitive to reconstructed image errors, both FBP and polyenergetic AM reconstruction are employed. Linear attenuation coefficients are estimated with residual errors of around 1% for energies of 30 keV to 1 MeV with errors rising to 3%-6% at lower energies down to 10 keV. In the ideal phantom geometry used here, the main advantage of AM reconstruction is less random cross-section uncertainty due to the improved noise performance.
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Darrell, Alexander Louis. "Image reconstruction for emission optical projection tomography." Thesis, University of Oxford, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.566048.
Full textAbstract:
Emission Optical Projection Tomography (eO PT) is a relatively new imag- ing modality that bridges a gap between micro Magnetic Resonance Imag- ing and Confocal Laser Scanning Microscopy. eO PT can be used to image the anatomy and gene expression of intact biological specimens at high resolution and thus provides an alternative to time consuming methods such as serial sectioning. Tomographic image reconstruction for eOPT is currently performed using the Filtered Back Projection algorithm which, while being fast, does not account for the physics of image formation and thus can result in reconstructions of reduced resolution and questionable quantitative consistency. This thesis describes work that was done on eOPT in three areas, including image formation, tomographic reconstruction, and memory savings, the latter of which were required to bring implementation of 3D iterative reconstruction algorithms within reach for the relatively high-resolution eO PT imaging modality. In the area of image formation, measurements were taken to reveal the effects of optical blurring, diffraction and charge-coupled device (CCD) camera noise. Accurate models of each of these phenomena were developed and compared against the measurements. The subject of image reconstruction was first addressed with a modi- fication to the FBP algorithm designed to correct for the quantitative inaccuracies suspected of being introduced by the FBP algorithm when reconstructing specimens consisting of very fine detail. This was done by incorporating the quantitative aspects of the model of image formation into the FBP algorithm. The full model of image formation was incorpo- rated into the iterative Maximum Likelihood Expectation Maximisation (MLEM) algorithm. The third strand of this thesis focuses on various memory saving meth- ods developed to enable the implementation and testing of a variation of MLEM known as the Ordered Subsets Expectation Maximisation (OSEM). , Without such memory saving methods, the implementation of an iterative 3D reconstruction algorithm such as MLEM or OSEM using a full model of image formation would have remained beyond the capacity of modern computers for the foreseeable future, requiring several Terabytes of RAM. Comparisons were made between the quality of and the time required to produce FBP and OSEM reconstructions of the same data sets given the availability of limited computing resources. The feasibility of adopting OSEM reconstructions as an alternative to FBP reconstructions was dis- cussed, based on the use of currently available cutting edge computing hardware.
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Zhang, Donghao. "Biomedical Image Analysis with Segmentation and Reconstruction." Thesis, University of Sydney, 2020. https://hdl.handle.net/2123/23685.
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The biomedical image segmentation plays an important role in cancer diagnosis. Cell segmentation and brain tumor are important subtopics of biomedical image segment- ation. Manual annotation of biomedical image is time-consuming and suffers from observer bias. We propose two cell segmentation methods based on convolutional neural network. The first cell segmentation method employs both generator and dis- criminator to obtain dual-contour enhanced predictions. The predictions are further processed by watershed algorithm. The post-processing technique is still required and not learning based which constrains its capability of being robust and general to other dataset. Based on the above disadvantage, we propose an end-to-end con- volutional neural network segmentation architecture. In terms of this architecture, semantic branch and instance branch are jointly trained with the shared backbone. When accurate segmentation architectures are available, designing an efficient seg- mentation architecture is in great need. We design a segmentation network with dilated depthwise separable convolution block as its fundamental component and evaluate its performance on brain tumor segmentation dataset. Curvilinear structure appears at both natural and artificial objects. For example, the vessel structure of human body and aerial road map are categorized as curvilinear structure. Reconstruction of neuronal axon and dendrites is significant to conduct morphometric analysis and understand working mechanism of human brain. Many methods were proposed to tackle with neuron reconstruction, but they fail to propose an effective solution of reconstructing large-scale neuron image. An adaptive tracing method is designed to trace large 3D volume block by block. In addition, graph neural network based vessel reconstruction method is applied to remove redundant tracing points of vessel reconstruction.
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Butterfield, S. "Reconstruction of extended environments from image sequences." Thesis, University of Leeds, 1997. http://etheses.whiterose.ac.uk/1269/.
Full textAbstract:
The automatic recovery of the three-dimensional structure of a scene from a sequence of two-dimensional images has been the subject of considerable research in the field of machine vision, with applications as wide-ranging as object recognition, virtual reality and robot navigation. Traditional attempts to solve this structure from motion (SFM) problem rely on calibrated cameras and involve the detection and tracking of features through successive images in the sequence. When considering long image sequences, taken with an ordinary hand-held video camera, the problem is significantly harder, since both camera calibration parameters and matched feature information are difficult to obtain accurately. An additional complication is that small errors in the recovered structure will accumulate over long sequences, possibly resulting in a reconstruction which is internally inconsistent. To date, there has been no discussion in the SFM literature of attempts to tackle this important issue. Recently, a number of different techniques have been developed for scene reconstruction using uncalibrated cameras. In such cases the recovered structure is correct up to projective transformation of the real structure. In this thesis, an original, incremental reconstruction system id described, based on this calibrated approach. A novel implementation for computing the fundamental matrix from a pair of images is presented, from which a projective reconstruction is obtained. For the first image pair in sequences, a small number of ground truth points are used to upgrade from projective to Eudlidean structure. This structure is propagated through successive frames to obtain a complete Euclidean reconstruction for the entire scene. The inconsistency problem is addressed by attempting to detect when previously viewed sections of the scene are re-encountered. A solution method using the geometric hashing model-based object recognition paradigm is proposed.
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Cabrera, Vives Guillermo. "Bayesian Image Reconstruction Based on Voronoi Diagrams." Tesis, Universidad de Chile, 2008. http://repositorio.uchile.cl/handle/2250/101966.
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Patty, Spencer R. "3D Image Reconstruction and Level Set Methods." BYU ScholarsArchive, 2011. https://scholarsarchive.byu.edu/etd/2812.
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We give a concise explication of the theory of level set methods for modeling motion of an interface as well as the numerical implementation of these methods. We then introduce the geometry of a camera and the mathematical models for 3D reconstruction with a few examples both simulated and from a real camera. We finally describe the model for 3D surface reconstruction from n-camera views using level set methods.
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MASSA, PAOLO. "Image reconstruction methods for Solar Orbiter STIX." Doctoral thesis, Università degli studi di Genova, 2022. http://hdl.handle.net/11567/1082766.
Full textAbstract:
The Spectrometer/Telescope for Imaging X-rays (STIX) is the instrument of the Solar Orbiter mission conceived for the observation of the X-ray radiation emitted during solar flares. STIX adopts an indirect imaging technique based on the use of modulation collimators, i.e., pairs of grids mounted in front of detectors. By measuring the modulated X-ray photon flux, the telescope provides the complex values of 30 Fourier components of the angular distribution of the X-ray source, named visibilities. Hence, the imaging problem for STIX is the inverse problem of reconstructing the image of the flaring X-ray source from a sparse sampling of its Fourier transform.
In this thesis, we describe the STIX imaging concept and the image reconstruction problem both from visibilities and from photon count measurements. We present different image reconstruction techniques: the count-based Expectation Maximization (EM) algorithm, the visibility-based maximum entropy method MEM_GE and a neural network approach for parametric image reconstruction. We test these methods on synthetic STIX data and, in the case of MEM_GE, on real data provided by the Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI). We propose a stopping rule for EM based on a predictive risk estimator. This estimator is derived by using a Poisson counterpart of Stein’s lemma for Gaussian variates. We validate the performance of the stopping rule in the case of the STIX imaging problem from synthetic data and in the case of a deconvolution inverse problem. Finally, we present the results of the STIX imaging problem from real data. We describe the first approaches of image reconstruction from semi-calibrated data, i.e., visibility amplitudes only. Then, we provide an overview of the visibility phase calibration, and we show the reconstructions from fully-calibrated visibilities obtained by using several methods, including MEM_GE and EM. The STIX reconstructions are validated by comparison with maps of the same events provided by the Atmospheric Imaging Assembly on board the Solar Dynamic Observatory (SDO/AIA) in UV wavelengths.
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Jiang, Qin. "Stereo image sequence compression." Diss., Georgia Institute of Technology, 2000. http://hdl.handle.net/1853/15634.
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Pai, Hung-ta. "Multichannel blind image restoration /." Digital version accessible at:, 1999. http://wwwlib.umi.com/cr/utexas/main.
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Mihir, Kandepu Abhignana, and Konduru Vinay Kumar. "3D Image Reconstruction Using Multiple Images." Thesis, 2015. http://ethesis.nitrkl.ac.in/6761/1/3D_MIHIR_2015.pdf.
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The point in this thesis is to use a robot using which we can get photographs of a given thing from known edges. We mean to repeat and model these 2D photos to get the 3D sort of the article, which will be created and demonstrated in MATLAB. Demonstrating of 3D items from different pictures is one of the testing undertakings. Therefore our endeavor does not keep itself to giving the customer the adaptability of survey the article at any edge and in any presentation however outfits him with the complete model in space. This is an approach which retrieves the calibration from the image sequence only. A 3D image reconstruction strategy from stereo pictures is displayed next that needs insignificant mediation from the client .The upside of this framework is that the stereo pictures don't have to be calibrated to acquire a remaking. Results for both the cam alignment and reproduction are displayed to confirm that it is conceivable to acquire a 3D model specifically from features of pictures 3D reproduction and demonstrating is utilized as a part of numerous fields like Virtual Reality, perceiving and controlling items and so on.
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Boora, Shivaprasad. "3D Image Reconstruction from Multiview Images." Thesis, 2017. http://ethesis.nitrkl.ac.in/8892/1/2017_MT_SBoora.pdf.
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This thesis presents an efficient method to reconstruct 3D point cloud from an arbitrary number of views of an object of interest. Nowadays, Light Detection and Ranging (LIDAR) devices are used in autonomous vehicles and robots to get the 3D measurements. LIDAR contains laser scanners which directly gives the 3D information. However, these scanners are very expensive and prone to interferences and noise due to bulk hardware present in the device. To address this problem, mobile phone cameras are used in the proposed method as they are lighter and cheaper compared to scanners. Multiviews of an object of interest are obtained using a mobile phone camera and they are given as input to the structure from motion (SFM) algorithm. In this algorithm, an appropriate set of mixed feature extraction techniques are employed to get good number of 3D inlier points. The obtained results are visualised as 3D point clouds.
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"Reconstruction of parallel MRI images using high resolution image reconstruction techniques." 2010. http://library.cuhk.edu.hk/record=b5894431.
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Tai, Chi Kin.Thesis (M.Phil.)--Chinese University of Hong Kong, 2010.
Includes bibliographical references (p. 56-59).
Abstracts in English and Chinese.
Chapter 1 --- Introduction --- p.7
Chapter 2 --- Theoretical Background --- p.9
Chapter 2.1 --- Nuclear Magnetic Resonance --- p.9
Chapter 2.1.1 --- Nuclear spin and macroscopic magnetization --- p.10
Chapter 2.1.2 --- Precession and Larmor Frequency --- p.12
Chapter 2.1.3 --- Radio-frequency excitation --- p.13
Chapter 2.1.4 --- Radio-frequency relaxation --- p.15
Chapter 2.1.5 --- Spin echoes --- p.17
Chapter 2.1.6 --- Contrast mechanisms --- p.17
Chapter 2.2 --- Magnetic Resonance Imaging --- p.20
Chapter 2.2.1 --- MRI machine hardware --- p.20
Chapter 2.2.2 --- Slice selection --- p.22
Chapter 2.2.3 --- Frequency encoding --- p.23
Chapter 2.2.4 --- Phase encoding --- p.26
Chapter 2.2.5 --- Pulse sequences --- p.26
Chapter 2.2.6 --- Field of view and resolution --- p.28
Chapter 3 --- Parallel Magnetic Resonance Imaging --- p.30
Chapter 3.1 --- Motivation --- p.30
Chapter 3.1.1 --- Aliasing --- p.31
Chapter 3.2 --- Coil array and coil sensitivities --- p.32
Chapter 3.3 --- Sensitivity encoding --- p.32
Chapter 3.3.1 --- Estimation of coil sensitivities --- p.33
Chapter 3.3.2 --- SENSE reconstruction --- p.33
Chapter 3.4 --- pMRI reconstruction by TV regularization --- p.35
Chapter 3.4.1 --- Model for coil images --- p.35
Chapter 3.4.2 --- Total variation-regularization approach --- p.36
Chapter 4 --- Reconstruction Results --- p.39
Chapter 4.1 --- Simulation --- p.39
Chapter 4.1.1 --- Reconstruction quality --- p.41
Chapter 4.1.2 --- Reconstruction results --- p.43
Chapter 4.2 --- MRI phantom experiments --- p.44
Chapter 4.2.1 --- Reconstruction quality --- p.48
Chapter 4.2.2 --- Reconstruction results --- p.49
Chapter 4.3 --- In-vivo MRI images --- p.51
Chapter 5 --- Discussions and Conclusions --- p.54
Bibliography --- p.56
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Stolle, Frank R. "Multi-image reconstruction from aerial images and sequences." 2006. https://scholarworks.umass.edu/dissertations/AAI3242385.
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Three-dimensional models of the environment have many current uses and great potential applications for intelligence operations, biological sciences, and city planning. How best to accurately and efficiently recover the three-dimensional structure of a scene from a number of two-dimensional aerial images and additional contextual information, however, represents a significant and challenging problem. Sensor data are now widely available from aerial surveys, autonomous aerial vehicles, or other sources. Traditionally, image-space stereo algorithms have been used to turn this data into usable three-dimensional information such as digital elevation models. We contend that a better methodology should involve the use of all available images simultaneously, as well as additional information from other sources, and propose a matching scheme that adjusts a surface model in a world coordinate system (object space) via an optimization process. A cost function is applied in a local surface optimization to minimize the differences between the object-space model and the image data at each location on the surface, taking into account other constraints. We apply constraints due to prior knowledge about the scene as well as resource constraints imposed by limited computational resources. Our model is recovered in a flexible and powerful representation that has already seen wide use in modeling for Computer Aided Design and Manufacturing (CAD/CAM): non-uniform rational B-splines (NURBS).
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"Image reconstruction with multisensors." 1998. http://library.cuhk.edu.hk/record=b5889642.
Full textAbstract:
by Wun-Cheung Tang.Thesis (M.Phil.)--Chinese University of Hong Kong, 1998.
Includes bibliographical references.
Abstract also in Chinese.
Abstracts --- p.1
Introduction --- p.3
Toeplitz and Circulant Matrices --- p.3
Conjugate Gradient Method --- p.6
Cosine Transform Preconditioner --- p.7
Regularization --- p.10
Summary --- p.13
Paper A --- p.19
Paper B --- p.36