Готові списки джерел за темами / Digital image restoration

Добірка наукової літератури з теми "Digital image restoration"

Автор: Grafiati
Опубліковано: 10 грудня 2022
Оновлено: 29 січня 2023

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Статті в журналах з теми "Digital image restoration"

1

Banham, M. R., and A. K. Katsaggelos. "Digital image restoration." IEEE Signal Processing Magazine 14, no. 2 (March 1997): 24–41. http://dx.doi.org/10.1109/79.581363.

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2

Kirkland, Earl J. "Digital restoration of ADF-STEM images." Proceedings, annual meeting, Electron Microscopy Society of America 46 (1988): 832–33. http://dx.doi.org/10.1017/s0424820100106223.

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Анотація:
Frieden and Wells have derived a maximum likelihood (ML) image restoration algorithm that accurately models the noise in each image element using Poisson counting statistics. This method also leads naturally to “maximum entropy” like ideas. They have reported a rather dramatic resolution enhancement when this method was applied to low light level astronomical images in which the image noise was essentially due to photon counting statistics. This low light level situation also accurately models the ADF (annular dark field) STEM (scanning transmission microscope) image if the image is aquired digitally by electronically counting the individual scattered electrons for each position of the focused probe.The simplest ADF-STEM image model assumes that the electron intensity distribution in the focused probe is the incoherent point spread function (psf) of the image.where g(x)=recorded image, f(x)=ideal image, n(x)=random noise, * represents convolution and
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3

Chen, Wei, Tingzhu Sun, Fangming Bi, Tongfeng Sun, Chaogang Tang, and Biruk Assefa. "Overview of Digital Image Restoration." Journal of New Media 1, no. 1 (2019): 35–44. http://dx.doi.org/10.32604/jnm.2019.05803.

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4

Lam, E. Y. "Image restoration in digital photography." IEEE Transactions on Consumer Electronics 49, no. 2 (May 2003): 269–74. http://dx.doi.org/10.1109/tce.2003.1209513.

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5

Chauhan, Vimal. "Reduction of Noise in Restoration of Images Using Mean and Median Filtering Techniques." International Journal for Research in Applied Science and Engineering Technology 9, no. 9 (September 30, 2021): 301–13. http://dx.doi.org/10.22214/ijraset.2021.37965.

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Анотація:
Abstract: The purpose of this paper is to present a study of digital technology approaches to image restoration. This process of image restoration is crucial in many areas such as satellite imaging, astronomical image & medical imaging where degraded images need to be repaired Personal images captured by various digital cameras can easily be manipulated by a variety of dedicated image processing algorithms [2]. Image restoration can be described as an important part of image processing technique. Image restoration has proved to be an active field of research in the present days. The basic objective is to enhance the quality of an image by removing defects and make it look pleasing [2]. In this paper, an image restoration algorithm based on the mean and median calculation of a pixel has been implemented. We focused on a certain iterative process to carry out restoration. The algorithm has been tested on different images with different percentage of salt and pepper noise. The improved PSNR and MSE values has been obtained. Keywords: De-Noising, Image Filtering, Mean Filter & Median Filter, Salt and Pepper Noise, Denoising Techniques, Image Restoration.
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6

Andono, Pulung Nurtantio, and Christy Atika Sari. "Remove Blur Image Using Bi-Directional Akamatsu Transform and Discrete Wavelet Transform." Scientific Journal of Informatics 9, no. 2 (November 17, 2022): 179–88. http://dx.doi.org/10.15294/sji.v9i2.34173.

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Анотація:
Purpose: Image is an imitation of everything that can be materialized, and digital images are taken using a machine. Although digital image capture uses machines, digital images are not free from interference. Image restoration is needed to restore the quality of the damaged image.Methods: Bi-directional Akamatsu Transform is proven to have an effective performance in reducing blur in images. Meanwhile, Discrete Wavelet Transform has been widely used in digital image processing research. We had been investigated the image restoration method by combining Bi-directional Akamatsu Transform and Discrete Wavelet Transform. Bi-directional Akamatsu Transform applied in Low-Low (LL) sub-band is the Discrete Wavelet Transform decomposition image most similar to the original image before decomposing. In this study, there are still shortcomings, including the determination of the values of N, up_enh, and down_enh, which are still manual. Manually setting the three values makes the Bi-directional Akamatsu Transform method not get the best results. With the use of machine learning methods can get better restoration results. Further testing is also needed for a more diverse and robust blur. The image data has a resolution of 256x256, 512x512, and 1024x1024. The image will be directly converted to a grey-scale image. The converted image will be given an attack model: average blur, gaussian blur, and motion blur. The image that has been attacked will apply two restoration methods: the proposed method and the Bi-direction Akatamatsu Transform. These two restoration images will then be compared using PSNR.Result: The average PSNR value from the restoration of the proposed method is 0.1446 higher than the average PSNR value from the restoration of the Bi-directional Akamatsu Transform method. When we compare it with the average PSNR value of the Akamatsu Transform restoration method, the average PSNR of the proposed method is 0.2084.Value: The combination of DWT and akamatsu transform results produce good PSNR values even though they have gone through the blurring method in image restoration.
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Du, Hua Yue, Yong Qian, Cheng Guo Wu, Yan Hua Huang, and Xia Li. "Digital Image Restoration in Microscopic Measurement." Applied Mechanics and Materials 421 (September 2013): 421–26. http://dx.doi.org/10.4028/www.scientific.net/amm.421.421.

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Анотація:
The requirement of the accuracy of microscopic measurements becomes more and more high, and traditional methods have been unable to meet the demands. Digital image deconvolution techniques are applied in microscopic measurement. By fabricating a pointolite, the point spread function of the optical system is measured, and then the geometric blurring in traditional microscopy is removed by using the maximum likelihood estimation algorithms and iteration threshold segmentation algorithms. The technique is applied to measure the total content of perlite and spheroidal graphite in spheroidal graphite iron accurately and easily, and then to measure the area of a scratch scaled in 10 microns on a medical department of orthopedics plates. The technique makes great sense in the development of corresponding measurement.
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8

Amudha, J., N. Pradeepa, and R. Sudhakar. "A Survey on Digital Image Restoration." Procedia Engineering 38 (2012): 2378–82. http://dx.doi.org/10.1016/j.proeng.2012.06.284.

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9

Ding, Yongsheng, Yunbo Wei, Shuisheng Zhang, and Shihang Yu. "Digital Image Restoration Based on Multicontour Batch Scanning." Scanning 2022 (September 5, 2022): 1–8. http://dx.doi.org/10.1155/2022/8106516.

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Анотація:
In order to explore the problem of digital image restoration, the authors propose a research on digital image restoration based on multicontour batch scanning. This method recommends key technical problems and solutions based on information represented by multicontour batch scans, exploring research in digital image restoration. Research has shown that the research on digital image restoration based on multicontour batch scanning is about 40% more efficient than traditional methods. Aiming at the new application of digital image inpainting, the application of image inpainting in image compression is studied in depth, and the technical principles of image inpainting and image compression are complemented.
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10

Nugroho, Ginanjar Setyo, and Gulam Hazmin. "Perbandingan Algoritma untuk Mereduksi Noise pada Citra Digital." Journal of Information Technology Ampera 3, no. 2 (August 7, 2022): 159–74. http://dx.doi.org/10.51519/journalita.volume3.isssue2.year2022.page159-174.

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Анотація:
Image restoration is one of the stages in the field of Digital Image Processing. Image restoration is objective, in the sense that restoration techniques tend to be based on mathematical or probabillistic models of image degradation. The mathematical algorithm to reduce noise in digital images in this study uses 8 filtering algorithm methods. The purpose of this study is to compare 8 filtering algorithm and conclude which algorithm is the best for reducing noise in digital images. The method for generating noise uses Rayleigh Noise and Erlang (Gamma) Noise. The algorithm for reducing noise is Arithmetic Mean Filter, Geometric Mean Filter, Harmonic Mean Filter, Contraharmonic Mean Filter, Geometric Mean Filter, Harmonic Mean Filter, Contraharmonic Mean Filter, Median Filter, Maximum Filter, Minimum Filter, and Midpoint Filter. The measurement to determine which algorithm is the best using Root Mean Square Error (RMSE). Tests were carried out on 15 digital images by testing 1200 times. The conclusion of this study is that the best algorithm for noise reduction is Median Filter by resulting the smallest RMSE value of 6.0860942.
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Дисертації з теми "Digital image restoration"

1

Sandor, Viviana. "Wavelet-based digital image restoration." W&M ScholarWorks, 1998. https://scholarworks.wm.edu/etd/1539623937.

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Digital image restoration is a fundamental image processing problem with underlying physical motivations. A digital imaging system is unable to generate a continuum of ideal pointwise measurements of the input scene. Instead, the acquired digital image is an array of measured values. Generally, algorithms can be developed to remove a significant part of the error associated with these measure image values provided a proper model of the image acquisition system is used as the basis for the algorithm development. The continuous/discrete/continuous (C/D/C) model has proven to be a better alternative compared to the relatively incomplete image acquisition models commonly used in image restoration. Because it is more comprehensive, the C/D/C model offers a basis for developing significantly better restoration filters. The C/D/C model uses Fourier domain techniques to account for system blur at the image formation level, for the potentially important effects of aliasing, for additive noise and for blur at the image reconstruction level.;This dissertation develops a wavelet-based representation for the C/D/C model, including a theoretical treatment of convolution and sampling. This wavelet-based C/D/C model representation is used to formulate the image restoration problem as a generalized least squares problem. The use of wavelets discretizes the image acquisition kernel, and in this way the image restoration problem is also discrete. The generalized least squares problem is solved using the singular value decomposition. Because image restoration is only meaningful in the presence of noise, restoration solutions must deal with the issue of noise amplification. In this dissertation the treatment of noise is addressed with a restoration parameter related to the singular values of the discrete image acquisition kernel. The restoration procedure is assessed using simulated scenes and real scenes with various degrees of smoothness, in the presence of noise. All these scenes are restoration-challenging because they have a considerable amount of spatial detail at small scale. An empirical procedure that provides a good initial guess of the restoration parameter is devised.
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2

Hazra, Rajeeb. "Constrained least-squares digital image restoration." W&M ScholarWorks, 1995. https://scholarworks.wm.edu/etd/1539623865.

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The design of a digital image restoration filter must address four concerns: the completeness of the underlying imaging system model, the validity of the restoration metric used to derive the filter, the computational efficiency of the algorithm for computing the filter values and the ability to apply the filter in the spatial domain. Consistent with these four concerns, this dissertation presents a constrained least-squares (CLS) restoration filter for digital image restoration. The CLS restoration filter is based on a comprehensive, continuous-input/discrete- processing/continuous-output (c/d/c) imaging system model that accounts for acquisition blur, spatial sampling, additive noise and imperfect image reconstruction. The c/d/c model-based CLS restoration filter can be applied rigorously and is easier to compute than the corresponding c/d/c model-based Wiener restoration filter. The CLS restoration filter can be efficiently implemented in the spatial domain as a small convolution kernel. Simulated restorations are used to illustrate the CLS filter's performance for a range of imaging conditions. Restoration studies based, in part, on an actual Forward Looking Infrared (FLIR) imaging system, show that the CLS restoration filter can be used for effective range reduction. The CLS restoration filter is also successfully tested on blurred and noisy radiometric images of the earth's outgoing radiation field from a satellite-borne scanning radiometer used by the National Aeronautics and Space Administration (NASA) for atmospheric research.
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3

Ahtaiba, Ahmed Mohamed A. "Restoration of AFM images using digital signal and image processing." Thesis, Liverpool John Moores University, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.604322.

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Анотація:
All atomic force microscope (AFM) images suffer from distortions, which are principally produced by the interaction between the measured sample and the AFM tip. If the three-dimensional shape of the tip is known, the distorted image can be processed and the original surface form ' restored' typically by deconvolution approaches. This restored image gives a better representation of the real 3D surface or the measured sample than the original distorted image. In this thesis, a quantitative investigation of using morphological deconvolution has been used to restore AFM images via computer simulation using various computer simulated tips and objects. This thesis also presents the systematic quantitative study of the blind tip estimation algorithm via computer simulation using various computer simulated tips and objects. This thesis proposes a new method for estimating the impulse response of the AFM by measuring a micro-cylinder with a-priori known dimensions using contact mode AFM. The estimated impulse response is then used to restore subsequent AFM images, when measured with the same tip, under similar measurement conditions. Significantly, an approximation to what corresponds to the impulse response of the AFM can be deduced using this method. The suitability of this novel approach for restoring AFM images has been confirmed using both computer simulation and also with real experimental AFM images. This thesis suggests another new approach (impulse response technique) to estimate the impulse response of the AFM. this time from a square pillar sample that is measured using contact mode AFM. Once the impulse response is known, a deconvolution process is carried out between the estimated impulse response and typical 'distorted' raw AFM images in order to reduce the distortion effects. The experimental results and the computer simulations validate the performance of the proposed approach, in which it illustrates that the AFM image accuracy has been significantly improved. A new approach has been implemented in this research programme for the restoration of AFM images enabling a combination of cantilever and feedback signals at different scanning speeds. In this approach, the AFM topographic image is constructed using values obtained by summing the height image that is used for driving the Z-scanner and the deflection image with a weight function oc that is close to 3. The value of oc has been determined experimentally using tri al and error. This method has been tested 3t ten different scanning speeds and it consistently gives more faithful topographic images than the original AFM images.
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4

Katsaggelos, Aggelos Konstantinos. "Constrained iterative image restoration algorithms." Diss., Georgia Institute of Technology, 1985. http://hdl.handle.net/1853/15830.

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5

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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6

MORGAN, KEITH PATRICK. "IMPROVED METHODS OF IMAGE SMOOTHING AND RESTORATION (NONSTATIONARY MODELS)." Diss., The University of Arizona, 1985. http://hdl.handle.net/10150/187959.

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Анотація:
The problems of noise removal, and simultaneous noise removal and deblurring of imagery are common to many areas of science. An approach which allows for the unified treatment of both problems involves modeling imagery as a sample of a random process. Various nonstationary image models are explored in this context. Attention is directed to identifying the model parameters from imagery which has been corrupted by noise and possibly blur, and the use of the model to form an optimal reconstruction of the image. Throughout the work, emphasis is placed on both theoretical development and practical considerations involved in achieving this reconstruction. The results indicate that the use of nonstationary image models offers considerable improvement over traditional techniques.
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7

Hamed, Mahmoud S. "Film and video restoration using nonlinear digital image processing techniques." Thesis, University of Strathclyde, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.400321.

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8

Revelant, Ivan L. "Restoration of images degraded by systems of random impulse response." Thesis, University of British Columbia, 1987. http://hdl.handle.net/2429/26731.

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The problem of restoring an image distorted by a system consisting of a stochastic impulse response in conjuction with additive noise is investigated. The method of constrained least squares is extended to this problem, and leads to the development of a new technique based on the minimization of a weighted error function. Results obtained using the new method are compared with those obtained by constrained least squares, and by the Wiener filter and approximations thereof. It is found that the new technique, "Weighted Least Squares", gives superior results if the noise in the impulse response is comparable to or greater than the additive noise.
Applied Science, Faculty of
Electrical and Computer Engineering, Department of
Graduate
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9

BRUEGGE, THOMAS JOSEPH. "THE USE OF FINITE IMPULSE RESPONSE KERNELS FOR IMAGE RESTORATION." Diss., The University of Arizona, 1985. http://hdl.handle.net/10150/187974.

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This dissertation examines the suitability of Display-Processor (DP) image computers for image enhancement and restoration tasks. Because the major architectural feature of the DP devices is their ability to rapidly evaluate finite impulse response (FIR) convolutions, much of the study focusses on the use of spatial-domain FIR convolutions to approximate Fourier-domain filtering. When the enhancement task requires the evaluation of only a single convolution, it is important that the FIR kernel used to implement the convolution is designed so that the resulting output is a good approximation of the desired output. A Minimum-Mean-Squared-Error design criterion is introduced for the purpose of FIR kernel design and its usefulness is demonstrated by showing some results of its use. If the restoration or enhancement task requires multiple convolutions in an iterative algorithm, it is important to understand how the truncation of the kernel to a finite region of support will affect the convergence properties of an algorithm and the output of the iterative sequence. These questions are examined for a limited class of nonlinear restoration algorithms. Because FIR convolutions are most efficiently performed on computing machines that have limited precision and are usually limited to performing fixed-point arithmetic, the dissertation also examines the effects of roundoff error on output images that have been computed using fixed point math. The number of bits that are needed to represent the data during a computation is algorithm dependent, but for a limited class of algorithms, it is shown that 12 bits are sufficient. Finally, those architectural features in a DP that are necessary for useful enhancement and restoration operations are identified.
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10

Burger, R. E. "Investigations relating to the computer restoration of ultrasonic sector scan images." Thesis, University of Cambridge, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.233704.

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This dissertation describes the application of maximum entropy image restoration to envelope-detected ultrasonic sector scans. The maximum entropy restoration of the image of a point target (phantom) test object is shown to be superior to results obtained from the more familiar Wiener filter. The subsequent application of maximum entropy to an in-vivo clinical ultrasound image, however, illustrates the pitfalls associated with determining the relative merit of an ultrasonic image restoration technique from test object results alone. Since the resolution of sector scan images is substantially worse in the lateral (azimuthal) scan direction than the axial scan direction, the deconvolution filters described in this thesis were applied in the lateral direction only. The maximum entropy method is shown to have certain inherent advantages over linear frequency-domain techniques for the restoration of ultrasonic sector scan images. The positivity constraint inherent in the maximum entropy method is shown to produce restorations with substantially fewer oscillatory artifacts than those produced by Wiener filtering. In addition, the iterative nature of the maximum entropy algorithm is shown to be compatible with the restoration of the undersampled regions in the far field of sector scan images. The restoration of sector scan images is complicated by the spatially varying degradation associated with such images. A novel approach to the restoration of this class of image degradation is presented in this thesis. The widespread use of maximum entropy image restoration has been inhibited by the technique's demanding computational requirements. This problem can be alleviated by the use of high speed computer hardware, and the final chapters of this thesis describe the design and construction of a microcomputer-based array processor. The advantages inherent in the use of such hardware are demonstrated with reference to the maximum entropy restoration of ultrasonic images.
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Книги з теми "Digital image restoration"

1

Katsaggelos, Aggelos K., ed. Digital Image Restoration. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-58216-5.

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1958-, Sezan M. Ibrahim, ed. Selected papers on digital image restoration. Bellingham, Wash., USA: SPIE Optical Engineering Press, 1992.

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3

Moayeri, Nader. An algorithm for blind restoration of blurred and noisy images. Palo Alto, CA: Hewlett-Packard Laboratories, Technical Publications Department, 1996.

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4

Zelensky, Alexander A., 1943- author and Kravchenko, Viktor F., 1939- author, eds. Bispectral methods of signal processing: Applications in radar, telecommunications and digital image restoration. Berlin: Walter de Gruyter GmbH & Co. KG, 2015.

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5

Medical image processing, reconstruction, and restoration: Concepts and methods. Boca Raton, FL: Taylor & Francis, 2006.

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6

R, Dougherty Edward, ed. Enhancement and restoration of digital documents: Statistical design of nonlinear algorithms. Bellingham, Wash., USA: SPIE Optical Engineering Press, 1997.

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7

Photoshop: Restoration & retouching. 2nd ed. Indianapolis, Ind: New Riders, 2004.

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8

Digital photo magic: Easy image retouching and restoration for librarians, archivists, and teachers. Medford, New Jersey: Information Today, Inc., 2016.

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9

Photo restoration and retouching using Corel PaintShop pro X4. 3rd ed. Boston, MA: Course Technology, CENGAGE Learning, 2012.

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10

Sebastiano, Battiato, and Gallo Giovanni 1962-, eds. Digital imaging for cultural heritage preservation: Analysis, restoration, and reconstruction of ancient artworks. Boca Raton: CRC Press, 2011.

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Частини книг з теми "Digital image restoration"

1

Sundararajan, D. "Image Restoration." In Digital Image Processing, 143–61. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-6113-4_5.

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Thanki, Rohit M., and Ashish M. Kothari. "Image Restoration." In Digital Image Processing using SCILAB, 71–98. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-89533-8_4.

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Jähne, Bernd. "Restoration and Reconstruction." In Digital Image Processing, 263–85. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-662-03477-4_9.

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Katsaggelos, Aggelos K. "Introduction." In Digital Image Restoration, 1–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-58216-5_1.

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Katsaggelos, Aggelos K. "A Dual Approach to Signal Restoration." In Digital Image Restoration, 21–56. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-58216-5_2.

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Katsaggelos, Aggelos K. "Hopfield-Type Neural Networks." In Digital Image Restoration, 57–88. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-58216-5_3.

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Katsaggelos, Aggelos K. "Compound Gauss-Markov Models for Image Processing." In Digital Image Restoration, 89–108. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-58216-5_4.

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8

Katsaggelos, Aggelos K. "Image Estimation Using 2D Noncausal Gauss-Markov Random Field Models." In Digital Image Restoration, 109–41. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-58216-5_5.

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Katsaggelos, Aggelos K. "Maximum Likelihood Identification and Restoration of Images Using the Expectation-Maximization Algorithm." In Digital Image Restoration, 143–76. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-58216-5_6.

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Katsaggelos, Aggelos K. "Nonhomogeneous Image Identification and Restoration Procedures." In Digital Image Restoration, 177–208. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-58216-5_7.

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Тези доповідей конференцій з теми "Digital image restoration"

1

Mishra, Reeturaj, Neetu Mittal, and Sunil Kumar Khatri. "Digital Image Restoration using Image Filtering Techniques." In 2019 International Conference on Automation, Computational and Technology Management (ICACTM). IEEE, 2019. http://dx.doi.org/10.1109/icactm.2019.8776813.

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Müller, Patrick, Matthias Lehmann, and Alexander Braun. "Optical quality metrics for image restoration." In Digital Optical Technologies II, edited by Bernard C. Kress and Peter Schelkens. SPIE, 2019. http://dx.doi.org/10.1117/12.2528100.

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3

Masnou, Simon, and Jean-Michel Morel. "Image restoration involving connectedness." In Sixth International Workshop on Digital Image Processing and Computer Graphics, edited by Emanuel Wenger and Leonid I. Dimitrov. SPIE, 1998. http://dx.doi.org/10.1117/12.301389.

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4

Wood, Lynnette, Robert A. Schowengerdt, and Dave Meyer. "Restoration For Sampled Imaging Systems." In Applications if Digital Image Processing IX, edited by Andrew G. Tescher. SPIE, 1986. http://dx.doi.org/10.1117/12.976236.

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5

Mickhayluck, Y. P., and D. V. Nacharov. "General method of digital image restoration." In 2010 20th International Crimean Conference "Microwave & Telecommunication Technology" (CriMiCo 2010). IEEE, 2010. http://dx.doi.org/10.1109/crmico.2010.5632966.

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6

Feigin, Gavriel, Nissim Ben-Yosef, and Steven Lashansky. "Adaptive Digital Defocus Image Restoration Filter." In 31st Annual Technical Symposium, edited by Andrew G. Tescher. SPIE, 1988. http://dx.doi.org/10.1117/12.942106.

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7

Du, Huayue, Yong Qian, Suhong He, Chengguo Wu, Yanhua Huang, and Xia Li. "Microscopic measurement using digital image restoration." In 2013 9th International Conference on Natural Computation (ICNC). IEEE, 2013. http://dx.doi.org/10.1109/icnc.2013.6818198.

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8

Prasad, S. "Optical preconditioning and digital image restoration." In Optics & Photonics 2005, edited by Victor L. Gamiz and Paul S. Idell. SPIE, 2005. http://dx.doi.org/10.1117/12.620170.

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"IMAGE RESTORATION - A New Explicit Approach in Filtering and Restoration of Digital Images." In International Conference on Security and Cryptography. SciTePress - Science and and Technology Publications, 2007. http://dx.doi.org/10.5220/0002140501960199.

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10

Rosenthaler, L. "Restoration of movie films by digital image processing." In IEE Seminar Digital Restoration of Film and Video Archives. IEE, 2001. http://dx.doi.org/10.1049/ic:20010026.

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