Rozprawy doktorskie na temat „Discrete cosine transforms (DCTs)”

Of the many existing eukaryotic gene finding software programs, none are able to guarantee accurate identification of genomic protein coding regions and other biological signals central to pathway from DNA to the protein. Eukaryotic gene finding is difficult mainly due to noncontiguous and non-continuous nature of genes. Existing approaches are heavily dependent on the compositional statistics of the sequences they learn from and are not equally suitable for all types of sequences. This thesis firstly develops efficient digital signal processing-based methods for the identification of genomic protein coding regions, and then combines the optimum signal processing-based non-data-driven technique with an existing data-driven statistical method in a novel system demonstrating improved identification of acceptor splice sites. Most existing well-known DNA symbolic-to-numeric representations map the DNA information into three or four numerical sequences, potentially increasing the computational requirement of the sequence analyzer. Proposed mapping schemes, to be used for signal processing-based gene and exon prediction, incorporate DNA structural properties in the representation, in addition to reducing complexity in subsequent processing. A detailed comparison of all DNA representations, in terms of computational complexity and relative accuracy for the gene and exon prediction problem, reveals the newly proposed ?paired numeric? to be the best DNA representation. Existing signal processing-based techniques rely mostly on the period-3 behaviour of exons to obtain one dimensional gene and exon prediction features, and are not well equipped to capture the complementary properties of exonic / intronic regions and deal with the background noise in detection of exons at their nucleotide levels. These issues have been addressed in this thesis, by proposing six one-dimensional and three multi-dimensional signal processing-based gene and exon prediction features. All one-dimensional and multi-dimensional features have been evaluated using standard datasets such as Burset/Guigo1996, HMR195, and the GENSCAN test set. This is the first time that different gene and exon prediction features have been compared using substantial databases and using nucleotide-level metrics. Furthermore, the first investigation of the suitability of different window sizes for period-3 exon detection is performed. Finally, the optimum signal processing-based gene and exon prediction scheme from our evaluations is combined with a data-driven statistical technique for the recognition of acceptor splice sites. The proposed DSP-statistical hybrid is shown to achieve 43% reduction in false positives over WWAM, as used in GENSCAN.

This thesis presents novel research work on copyright protection of grey scale and colour digital images. New blind frequency domain watermarking algorithms using one dimensional and two dimensional Walsh coding were developed. Handwritten signatures and mobile phone numbers were used in this project as watermarks. In this research eight algorithms were developed based on the DCT using 1D and 2D Walsh coding. These algorithms used the low frequency coefficients of the 8 × 8 DCT blocks for embedding. A shuffle process was used in the watermarking algorithms to increase the robustness against the cropping attacks. All algorithms are blind since they do not require the original image. All algorithms caused minimum distortion to the host images and the watermarking is invisible. The watermark is embedded in the green channel of the RGB colour images. The Walsh coded watermark is inserted several times by using the shuffling process to improve its robustness. The effect of changing the Walsh lengths and the scaling strength of the watermark on the robustness and image quality were studied. All algorithms are examined by using several grey scale and colour images of sizes 512 × 512. The fidelity of the images was assessed by using the peak signal to noise ratio (PSNR), the structural similarity index measure (SSIM), normalized correlation (NC) and StirMark benchmark tools. The new algorithms were tested on several grey scale and colour images of different sizes. Evaluation techniques using several tools with different scaling factors have been considered in the thesis to assess the algorithms. Comparisons carried out against other methods of embedding without coding have shown the superiority of the algorithms. The results have shown that use of 1D and 2D Walsh coding with DCT Blocks offers significant improvement in the robustness against JPEG compression and some other image processing operations compared to the method of embedding without coding. The originality of the schemes enables them to achieve significant robustness compared to conventional non-coded watermarking methods. The new algorithms offer an optimal trade-off between perceptual distortion caused by embedding and robustness against certain attacks. The new techniques could offer significant advantages to the digital watermark field and provide additional benefits to the copyright protection industry.

Thesis (DSc (Mathematical Sciences. Applied Mathematics))--University of Stellenbosch, 2009.
The replacement of the standard discrete cosine transform (DCT) of JPEG with the windowed modifed DCT (MDCT) is investigated to determine whether improvements in numerical quality can be achieved. To this end, we employ an existing algorithm for optimal quantisation, for which we also propose improvements. This involves the modelling and prediction of quantisation tables to initialise the algorithm, a strategy that is also thoroughly tested. Furthermore, the effects of various window functions on the coding results are investigated, and we find that improved quality can indeed be achieved by modifying JPEG in this fashion.

Rapid evolution of digital technology has improved the ease of access to digital information enabling reliable, faster and efficient storage, transfer and processing of digital data. It also leads to the consequence of making the illegal production and redistribution of digital media easy and undetectable. Hence, the risk of copyright violation of multimedia data has increased due to the enormous growth of computer networks that provides fast and error free transmission of any unauthorized duplicate and possibly manipulated copy of multimedia information. One possible solution may be to embed a secondary signal or pattern into the image that is not perceivable and is mixed so well with the original digital data that it is inseparable and remains unaffected against any kind of multimedia signal processing. This embedded secondary information is digital watermark which is, in general, a visible or invisible identification code that may contain some information about the intended recipient, the lawful owner or author of the original data, its copyright etc. in the form of textual data or image. In order to be effective for copyright protection, digital watermark must be robust which are difficult to remove from the object in which they are embedded despite a variety of possible attacks. Several types of watermarking algorithms have been developed so far each of which has its own advantages and limitations. Among these, recently Singular Value Decomposition (SVD) based watermarking algorithms have attracted researchers due to its simplicity and some attractive mathematical properties of SVD. Here a number of pure and hybrid SVD based watermarking schemes have been investigated and finally a RST invariant modified SVD and Discrete Cosine Transform (DCT) based algorithm has been developed. A preprocessing step before the watermark extraction has been proposed which makes the algorithm resilient to geometric attack i.e. RST attack. Performance of this watermarking scheme has been analyzed by evaluating the robustness of the algorithm against geometric attack including rotation, scaling, translation (RST) and some other attacks. Experimental results have been compared with existing algorithm which seems to be promising.
Phone number: +88041730212

The goal of this project was to implement and compare Invere Discrete Cosine Transform using three methods i.e. by bit parallel, digit serial and bit serial. This application describes a one dimensional Discrete Cosine Transform by bit prallel method and has been implemented by 0.35 ìm technology. When implementing a design, there are several considerations like word length etc. were taken into account. The code was implemented using WHDL and some of the calculations were done in MATLAB. The VHDL code was the synthesized using Design Analyzer of Synopsis; power was calculated and the results were compared.

Discrete Cosine Transform (DCT) is widely used transform in many areas of the current information age. It is used in signal compression such as voice recognition, shape recognition and also in FBI finger prints. DCT is the standard compression system used in JPEG format. The DCT quality deteriorates at low-bit compression rate. The deterioration is due to the blocking artifact inherent in block DCT. One of the successful attempts to reduce these blocking artifacts was conversion of Block-DCT into Line-DCT. In this thesis we will explore the Line-DCT and introduce a new form of line-DCT called Bidirectional-DCT, which retains the properties of Line- DCT while improving computational efficiency. The results obtained in this thesis show significant reduction in processing time both in one dimensional and two dimensional DCT in comparison with the traditional Block-DCT. The quality analysis also shows that the least mean square error is considerably lower than the traditional Block-DCT which is a consequence of removing the blocking artifacts. Finally, unlike the traditional block DCT, the Bidirectional-DCT enables compression with very low bit rates and very low blocking artifacts.

This thesis deals with the development and evaluation of blind discrete cosine transform-based watermarking algorithms for copyright protection of digital still images using handwritten signatures and mobile phone numbers. The new algorithms take into account the perceptual capacity of each low frequency coefficients inside the Discrete Cosine Transform (DCT) blocks before embedding the watermark information. They are suitable for grey-scale and colour images. Handwritten signatures are used instead of pseudo random numbers. The watermark is inserted in the green channel of the RGB colour images and the luminance channel of the YCrCb images. Mobile phone numbers are used as watermarks for images captured by mobile phone cameras. The information is embedded multiple-times and a shuffling scheme is applied to ensure that no spatial correlation exists between the original host image and the multiple watermark copies. Multiple embedding will increase the robustness of the watermark against attacks since each watermark will be individually reconstructed and verified before applying an averaging process. The averaging process has managed to reduce the amount of errors of the extracted information. The developed watermarking methods are shown to be robust against JPEG compression, removal attack, additive noise, cropping, scaling, small degrees of rotation, affine, contrast enhancements, low-pass, median filtering and Stirmark attacks. The algorithms have been examined using a library of approximately 40 colour images of size 512 512 with 24 bits per pixel and their grey-scale versions. Several evaluation techniques were used in the experiment with different watermarking strengths and different signature sizes. These include the peak signal to noise ratio, normalized correlation and structural similarity index measurements. The performance of the proposed algorithms has been compared to other algorithms and better invisibility qualities with stronger robustness have been achieved.

The task of detecting human faces within either a still image or a video frame is one of the most popular object detection problems. For the last twenty years researchers have shown great interest in this problem because it is an essential pre-processing stage for computing systems that process human faces as input data. Example applications include face recognition systems, vision systems for autonomous robots, human computer interaction systems (HCI), surveillance systems, biometric based authentication systems, video transmission and video compression systems, and content based image retrieval systems. In this thesis, non-traditional methods are investigated for detecting human faces within color images or video frames. The attempted methods are chosen such that the required computing power and memory consumption are adequate for real-time hardware implementation. First, a standard color image database is introduced in order to accomplish fair evaluation and benchmarking of face detection and skin segmentation approaches. Next, a new pre-processing scheme based on skin segmentation is presented to prepare the input image for feature extraction. The presented pre-processing scheme requires relatively low computing power and memory needs. Then, several feature extraction techniques are evaluated. This thesis introduces feature extraction based on Two Dimensional Discrete Cosine Transform (2D-DCT), Two Dimensional Discrete Wavelet Transform (2D-DWT), geometrical moment invariants, and edge detection. It also attempts to construct a hybrid feature vector by the fusion between 2D-DCT coefficients and edge information, as well as the fusion between 2D-DWT coefficients and geometrical moments. A self organizing map (SOM) based classifier is used within all the experiments to distinguish between facial and non-facial samples. Two strategies are tried to make the final decision from the output of a single SOM or multiple SOM. Finally, an FPGA based framework that implements the presented techniques, is presented as well as a partial implementation. Every presented technique has been evaluated consistently using the same dataset. The experiments show very promising results. The highest detection rate of 89.2% was obtained when using a fusion between DCT coefficients and edge information to construct the feature vector. A second highest rate of 88.7% was achieved by using a fusion between DWT coefficients and geometrical moments. Finally, a third highest rate of 85.2% was obtained by calculating the moments of edges.
Master of Science

Cette thèse forme une contribution au problème de la conservation de l'énergie dans le cas particulier des réseaux de capteurs d'images, où une partie voire tous les nœuds du réseau sont équipés d'une petite caméra à technologie CMOS. Les images engagent des volumes de données très largement supérieurs aux mesures scalaires classiques telles que la température, et donc des dépenses énergétiques plus élevées. L'émetteur radio étant l'un des composants les plus gourmands en énergie, il est évident que la compression de l'image à la source peut réduire significativement l'énergie dépensée pour la transmission de l'image, tant au niveau du nœud caméra que des nœuds formant le chemin jusqu'au point de collecte. Toutefois, les méthodes de compression bien connues (JPEG, JPEG2000, SPIHT) sont mal adaptées à la limitation des ressources de calcul et de mémoire caractéristiques des nœuds-capteurs. Sur certaines plateformes matérielles, ces algorithmes ont même un coût énergétique supérieur au gain qu'ils amènent sur la transmission. Autrement dit, le nœud caméra épuise plus vite sa batterie en envoyant des images compressées que des images non compressées. La complexité de l'algorithme de compression est donc un critère de performance aussi important que le rapport débit-distorsion. Les contributions contenues dans ce mémoire de thèses sont triples : - Tout d'abord, nous avons proposé un algorithme de compression basé sur la transformée en cosinus discrète (DCT 8 points) de complexité réduite, combinant la méthode de DCT rapide la plus efficace de la littérature (DCT de Cordic-Loeffler) à une exécution réduite aux coefficients délimités par une zone carrée de taille k<8, les plus importants dans la reconstruction visuelle. Avec cette approche zonale, le nombre de coefficients à calculer, mais aussi à quantifier et encoder par bloc de 8x8 pixels est réduit à k^2 au lieu de 64, ce qui diminue mécaniquement le coût de la compression. - Nous avons ensuite étudié l'impact de k, donc du nombre de coefficients sélectionnés, sur la qualité de l'image finale. L'étude a été réalisée avec un jeu d'une soixantaine d'images de référence et la qualité des images était évaluée en utilisant plusieurs métriques, le PSNR, le PSNR-HVS et le MMSIM. Les résultats ont servi à identifier, pour un débit donné, la valeur limite de k qu'on peut choisir (statistiquement) sans dégradation perceptible de la qualité, et par conséquent les limites posées sur la réduction de la consommation d'énergie à débit et qualité constants. - Enfin, nous donnons les résultats de performances obtenus par des expérimentations sur une plateforme réelle composée d'un nœud Mica2 et d'une caméra Cyclops afin de démontrer la validité de nos propositions. Dans un scénario considérant des images de 128x128 pixels encodées à 0,5 bpp par exemple, la dépense d'énergie du nœud caméra (incluant compression et transmission) est divisée par 6 comparée au cas sans compression, et par 2 comparée au cas de l'algorithme JPEG standard.

La demande des usagers en termes de débit, de couverture et de qualité de service croît exponentiellement, avec une demande de plus en plus accrue en énergie électrique pour assurer les liaisons entre les réseaux. Dans ce contexte, les nouvelles formes d’ondes basées sur la modulation OFDM se sont répandues et sont utilisées dans les récentes architectures de radiocommunications. Cependant, ces signaux sont très sensibles aux non-linéarités des amplificateurs de puissance à cause des fortes fluctuations d’enveloppe caractérisées par un fort PAPR qui dégrade le bilan énergétique et le rendement de l’émetteur. Dans ce travail de thèse, nous avons tout d’abord dressé un état de l’art des techniques de réduction du PAPR. Cette présentation nous a permis de proposer une nouvelle méthodologie basée sur les techniques d’entrelacement et de codage. Cette première contribution consiste en l’utilisation de la technique d’entrelacement, en faisant appel aux sous porteuses nulles pour la transmission des informations auxiliaires, tout en respectant les spécifications fréquentielles du standard utilisé. La deuxième contribution est basée sur la combinaison des deux techniques de Shaping et de Transformée en Cosinus Discrète DCT, dans l’objectif d’améliorer davantage les performances du système. Les résultats de simulation ont montré que l’utilisation de ces deux techniques permet un gain significatif en termes de réduction du PAPR, qui se traduit par l’amélioration du rendement. Enfin, nous avons présenté une étude expérimentale pour l’ensemble des techniques proposées afin de confirmer les résultats obtenus en simulation. Ces évaluations sont réalisées avec un banc d'essais de radiocommunications pour le test d'un amplificateur de puissance commercial de technologie LDMOS de 20W, fonctionnant à 3.7 GHz en classe AB. Les résultats obtenus pour les standards IEEE 802.11 montrent que ces nouvelles approches permettent de garantir la robustesse de transmission, d’améliorer la qualité des liaisons et d’optimiser la consommation électrique
The request of the users in terms of rate, coverage and quality of service is growing exponentially, with increasing demand for electrical energy, to ensure networks link. In this context, new waveforms based on the OFDM modulation become widely popular and used intensively in recent radio communications architectures. However, these signals are sensitive to the power amplifier nonlinearities because of their high envelope fluctuations characterized by a high PAPR, which degrades the energy consumption and the transmitter efficiency.In this thesis, we first began by a state art of the PAPR reduction techniques. This presentation allowed us to propose a new method based on interleaving and coding techniques. The first contribution consists on the use of the interleaving technique using null-subcarriers for the transmission of the side information, while respecting the frequency specifications of the used standard. The second one is based on the conjunction of the Shaping technique and the Discrete Cosine Transform (DCT), with the aim of improving the performance of the system. Simulation results show that the use of these two techniques allows a significant gain in terms of PAPR reduction, which results in the improvement of the system efficiency. Finally, we presented an experimental study of the proposed techniques using an RF test bench with a commercial LDMOS 20 W PA, class AB operating at 3.7 GHz. The results obtained for the IEEE 802.11 standards show that the proposed approaches allow the transmission robustness and quality, while optimizing the power consumption

Thesis deals with multimedia signal comparison of compression options focused on video and advanced codecs. Specifically it describes the encoding and decoding of video recordings according to the MPEG standard. The theoretical part of the thesis describes characteristic properties of the video signal and justification for the need to use recording and transmission compression. There are also described methods for elimination of encoded video signal redundancy and irrelevance. Further on are discussed ways of measuring the video signal quality. A separate chapter is focused on the characteristics of currently used and promising codecs. In the practical part of the thesis were created functions in Matlab environment. These functions were implemented into graphic user interface that simulates the activity of functional blocks of the encoder and decoder. Based on user-specified input parameters it performs encoding and decoding of any given picture, composed of images in RGB format, and displays the outputs of individual functional blocks. There are implemented algorithms for the initial processing of the input sequence including sub-sampling, as well as DCT, quantization, motion compensation and their inverse operations. Separate chapters are dedicated to the realisation of codec description in the Matlab environment and to the individual processing steps output. Further on are mentioned compress algorithm comparisons and the impact of parameter change onto the final signal. The findings are summarized in conclusion.

This thesis deals with lossless and losing methods of data compressions and their possible applications in the measurement engineering. In the first part of the thesis there is a theoretical elaboration which informs the reader about the basic terminology, the reasons of data compression, the usage of data compression in standard practice and the division of compression algorithms. The practical part of thesis deals with the realization of the compress algorithms in Matlab and LabWindows/CVI.

The first goal of diploma thesis is to study the basic principles of video signal compression. Introduction to techniques used to reduce irrelevancy and redundancy in the video signal. The second goal is, on the basis of information about compression tools, implement the individual compression tools in the programming environment of Matlab and assemble simple model of the video codec. Diploma thesis contains a description of the three basic blocks, namely - interframe coding, intraframe coding and coding with variable length word - according the standard MPEG-2.

Sun, Deqing.
Thesis (M.Phil.)--Chinese University of Hong Kong, 2007.
Includes bibliographical references (leaves 86-91).
Abstracts in English and Chinese.
Abstract --- p.i
摘要 --- p.iii
Contributions --- p.iv
Acknowledgement --- p.vi
Abbreviations --- p.xviii
Notations --- p.xxi
Chapter 1 --- Introduction --- p.1
Chapter 1.1 --- Image compression and postprocessing --- p.1
Chapter 1.2 --- A brief review of postprocessing --- p.3
Chapter 1.3 --- Objective and methodology of the research --- p.7
Chapter 1.4 --- Thesis organization --- p.8
Chapter 1.5 --- A note on publication --- p.9
Chapter 2 --- Background Study --- p.11
Chapter 2.1 --- Image models --- p.11
Chapter 2.1.1 --- Minimum edge difference (MED) criterion for block boundaries --- p.12
Chapter 2.1.2 --- van Beek's edge model for an edge --- p.15
Chapter 2.1.3 --- Fields of experts (FoE) for an image --- p.16
Chapter 2.2 --- Degradation models --- p.20
Chapter 2.2.1 --- Quantization constraint set (QCS) and uniform noise --- p.21
Chapter 2.2.2 --- Narrow quantization constraint set (NQCS) --- p.22
Chapter 2.2.3 --- Gaussian noise --- p.22
Chapter 2.2.4 --- Edge width enlargement after quantization --- p.25
Chapter 2.3 --- Use of these models for postprocessing --- p.27
Chapter 2.3.1 --- MED and edge models --- p.27
Chapter 2.3.2 --- The FoE prior model --- p.27
Chapter 3 --- Postprocessing using MED and edge models --- p.28
Chapter 3.1 --- Blocking artifacts suppression by coefficient restoration --- p.29
Chapter 3.1.1 --- AC coefficient restoration by MED --- p.29
Chapter 3.1.2 --- General derivation --- p.31
Chapter 3.2 --- Detailed algorithm --- p.34
Chapter 3.2.1 --- Edge identification --- p.36
Chapter 3.2.2 --- Region classification --- p.36
Chapter 3.2.3 --- Edge reconstruction --- p.37
Chapter 3.2.4 --- Image reconstruction --- p.37
Chapter 3.3 --- Experimental results --- p.38
Chapter 3.3.1 --- Results of the proposed method --- p.38
Chapter 3.3.2 --- Comparison with one wavelet-based method --- p.39
Chapter 3.4 --- On the global minimum of the edge difference . . --- p.41
Chapter 3.4.1 --- The constrained minimization problem . . --- p.41
Chapter 3.4.2 --- Experimental examination --- p.42
Chapter 3.4.3 --- Discussions --- p.43
Chapter 3.5 --- Conclusions --- p.44
Chapter 4 --- Postprocessing by the MAP criterion using FoE --- p.49
Chapter 4.1 --- The proposed method --- p.49
Chapter 4.1.1 --- The MAP criterion --- p.49
Chapter 4.1.2 --- The optimization problem --- p.51
Chapter 4.2 --- Experimental results --- p.52
Chapter 4.2.1 --- Setting algorithm parameters --- p.53
Chapter 4.2.2 --- Results --- p.56
Chapter 4.3 --- Investigation on the quantization noise model . . --- p.58
Chapter 4.4 --- Conclusions --- p.61
Chapter 5 --- Conclusion --- p.71
Chapter 5.1 --- Contributions --- p.71
Chapter 5.1.1 --- Extension of the DCCR algorithm --- p.71
Chapter 5.1.2 --- Examination of the MED criterion --- p.72
Chapter 5.1.3 --- Use of the FoE prior in postprocessing . . --- p.72
Chapter 5.1.4 --- Investigation on the quantization noise model --- p.73
Chapter 5.2 --- Future work --- p.73
Chapter 5.2.1 --- Degradation model --- p.73
Chapter 5.2.2 --- Efficient implementation of the MAP method --- p.74
Chapter 5.2.3 --- Postprocessing of compressed video --- p.75
Chapter A --- Detailed derivation of coefficient restoration --- p.76
Chapter B --- Implementation details of the FoE prior --- p.81
Chapter B.1 --- The FoE prior model --- p.81
Chapter B.2 --- Energy function and its gradient --- p.83
Chapter B.3 --- Conjugate gradient descent method --- p.84
Bibliography --- p.86

No
At present, almost all digital images are stored and transferred in their compressed format in which discrete cosine transform (DCT)-based compression remains one of the most important data compression techniques due to the efforts from JPEG. In order to save the computation and memory cost, it is desirable to have image processing operations such as feature extraction, image indexing, and pattern classifications implemented directly in the DCT domain. To this end, we present in this paper a generalized analysis of spatial relationships between the DCTs of any block and its sub-blocks. The results reveal that DCT coefficients of any block can be directly obtained from the DCT coefficients of its sub-blocks and that the interblock relationship remains linear. It is useful in extracting global features in compressed domain for general image processing tasks such as those widely used in pyramid algorithms and image indexing. In addition, due to the fact that the corresponding coefficient matrix of the linear combination is sparse, the computational complexity of the proposed algorithms is significantly lower than that of the existing methods.

碩士
國立高雄第一科技大學
電腦與通訊工程所
90
The Discrete Fourier Transform（DFT）has been widely applied in communcation, speech processing, image processing, radar and sonar systems, etc. The architecture of DFT implement can be classified into two fields：（1）one is a pipelined systolic architecture,（2）the other is a memory-based architecture. Discrete Cosine Transform（DCT）has been commonly adopted in the various atandardsfor image compression while FPGA has become a new trend of ASIC design, so we will apply FPGA techinque to implement the DFT and the DCT. This thesis deals with how to use FPGA techinque to implement： （1）the pipelined systolic array architecture that requires log2N complex multipliers, 2log2N complex adders, 2log2N multiplexers, N delay elements and is able to provide a throughput of one transform sample per clock cycle; （2）the memory-based architecture that consists of three two-port RAM’s, one ROM, one complex multiplier, two complex adders, one multiplexer, and has capability of computing one transform sample every log2N+1 clock cycles on average; （3）Improved architecture in（2）under increasing little hardware that spends half of run time, i.e.N(log2N)/2; （4）2D-DFT that use architecture in（2）of 1D-DFT; （5）DCT operation and 2D-DCT operation.

碩士
國立高雄第一科技大學
電腦與通訊工程所
90
The two dimensional discrete cosine transform (2D-DCT) is widely used in digital signal processing, particularly for digital image processing in high speed transmission. There are two classes to realize in hardware structure, including the direct method, and the indirect method which is also called row-column method. It is more efficient for using the direct method. However, due to the computational complexity, the row-column method still has been adopted in the hardware implementation. In the indirect method, one dimensional of the rows or columns DCT coefficient are computed in advance. Then, a transpose matrix is obtained, and the elements of the transpose matrix are saved in a transpose matrix register. By the pivoting the elements of rows and columns, the one dimensional DCT of the transpose matrix is computed again. From performing twice one dimensional DCT transformations, then a two dimensional DCT has been formulated. The processing steps of one dimensional DCT are as follows: (1)Transform the DCT matrix into two 4*4 matrix. Then, change the elements of non-input data to 1’s complements. There 1’s complements have special weight individually. (2)Eight coefficient matrices. Based on these eight coefficient matrices have been obtained by above processing step. The partial products of all DCT coefficient can be found out. In the implementation of the circuit, only 26 adders are needed. (3)From this partial products, by means of adder_shift or 4-2 compressor tree circuit, we sum up all partial products by individual can be gained weight. Thus one dimensional DCT coefficients can be obtained. Compare the architecture of this method with New Distributed Arithmetic Architecture technique(NEDA) structure published in 2000. Our adder s of 1D DCT needed can be reduced from 35 to 26 in the same bit rate. If the hardware is designed in pipelined processing, the speed will be more promoted. The delay time is only equal to the delay of 4-2 compressor tree and an adder.

碩士
中原大學
通訊工程碩士學位學程
103
In this thesis, we propose new transforms related to Random Discrete Fractional Cosine Transform and Random Discrete Fractional Sine Transform.They include the Real Random Discrete Fractional Cosine Transform and Real Random Discrete Fractional Sine Transform of types I、IV、V and VIII,which are real transforms of RDFRCT and RDFRST.We also propose the Random Generalized Discrete Fractional Fourier Transform and Random Generalized Discrete Fractional Hartley Transform matrices with reduced computations.They have the properties of fast algorithms,which reduce half computations of the RGDFRFT and RGDFRHT.These transforms are all random transforms so that they can be applied in image encryption and image watermarking.In image watermarking experiments,we find RDFRST of type VIII has the best robusteness.It can resist the largest region of cropping attack,such that it is the transform with best robusteness.

碩士
國立成功大學
電機工程學系碩博士班
92
This thesis focuses on the efficient implementation of the transform coding in video coding systems. It consists of two parts. In the first part, we propose a unified fixed-coefficient recursive structure for computing the general length discrete transforms. After regular preprocessing, the general discrete transforms are realized in a second-order infinite-impulse response (IIR) filter. The proposed recursive structure only requires half the recursive cycles and achieves more accurate results than the existing ones. The proposed algorithm can be applied to many popular transforms, such as subband synthesis filtering, inverse modified discrete cosine transform (IMDCT) and all discrete cosine transform (DCT) types. In the second part, high throughput hardware architectures for fast computation of the 4×4 transforms suggested in H.264 advanced video coders (AVC) are proposed. The proposed architectures could provide higher throughput rate and realize in a smaller chip area than the conventional row-column approaches. The proposed architectures are synthesized with TSMC 0.35 �慆 technology. The synthesized multiple transform architecture could process 800 M samples/sec at 100 MHz for all three transforms.

碩士
國立成功大學
電機工程學系
88
The MP3 audio format uses the MPEG-1 audio Layer 3, which is one of the most advanced MPEG (Moving Picture Experts Group) standards for digital audio compression. The MPEG-1 audio Layer 3 has been widely used in internet and wireless communication and storage applications. The modified discrete cosine transform (MDCT) and its inverse transform (IMDCT) are the most complex operations in the MPEG-1 Layer 3 audio coding standard. In this thesis, we propose the new recursive structures for computing MDCT and IMDCT. This recursive structure is based on finite impulse response filters (IIR). We can use several IIR structures for concurrent computing MDCT and IMDCT components. The advantages of the proposed recursive IIR structure are rapid computational efficiency and high throughput rate. With regularity and modularity, the proposed recursive MDCT and IMDCT figured is suitable for VLSI implementation. In this thesis, we also realize a VLSI chip, which can perform both of the efficient recursion algorithms by using COMPASS 0.35µm high performance cell library with TSMC SPQM 0.35µm process technology. The realized VLSI takes about 7.5k gates in 2mm 2mm silicon area. The measurement result shows that the chip can work at about 50MHz clock rate.

碩士
國立中山大學
資訊工程學系研究所
89
The thesis proposes using the efficient memory arrangement methods for the implementation of radix-r multi-dimensional Discrete Fourier Transform (DFT) and Discrete Cosine Transform (DCT). By using the memory instead of the registers to buffer and reorder data, hardware complexity is significantly reduced. We use the recursive architecture that requires only one arithmetic-processing element to compute the entire DFT/DCT operation. The algorithm is based on efficient coefficient matrix factorization and data allocation. By exploiting the features of Kronecker product representation in the fast algorithm, the multi-dimensional DFT/DCT operation is converted into its corresponding 1-D problem and the intermediate data is stored in several memory units. In addition to the smaller area, we also propose a method to reduce the power consumption of the DFT/DCT processors.

碩士
國立高雄師範大學
物理學系
96
This research presents a fast and accurate real-time optical auto-focusing system, which utilizes a frequency component of the discrete cosine transform (DCT) as the focus measure. Besides, a nonlinear regression routine is combined in the algorithm to quickly move a rotational stepper motor to the best focus. The concise and effective algorithm can be applied to digital cameras, microscopes and optical inspection instruments.

碩士
國立交通大學
電機與控制工程系
89
In this thesis, we present two new algorithms for computing the inverse modified discrete cosine transform(IMDCT) such that the computation complexity is equal to but the numerical performance is better than existing fast algorithms. To compute N-point IMDCT, the first algorithm is realized in the following sequence: multiplication of the N/2 input data by an N/2-value cosine sequence, N/2-point fast DCT, and a simple recursive addition. The second algorithm, closely reversing the computation procedures of the first algorithm, is realized in order by simple recursive addition, N/2-point IDCT, and multiplication of the IDCT output by an N/2-value cosine sequence. MDCT realization can be simply obtained by transposing the signal flow graph for evaluating the IMDCT. For the proposed two IMDCT algorithms, we have analyzed the realization complexity and simulated the fixed-point error. Comparing with the existing fast IMDCT algorithms in literature, we observe from the analysis and simulation results that the new algorithms have better numerical accuracy and thus can be realized with short word length, resulting in more efficient realization.

Modified discrete cosine transform (MDCT) derived from DCT IV has emerged as the most suitable choice for transform domain audio coding applications due to its time domain alias cancellation property and de-correlation capability. In the present research work, we focus on MDCT domain analysis of audio signals for compression and other applications. We have derived algorithms for linear filtering in DCT IV and DST IV domains for symmetric and non-symmetric filter impulse responses. These results are also extended to MDCT and MDST domains which have the special property of time domain alias cancellation. We also derive filtering algorithms for the DCT II and DCT III domains. Comparison with other methods in the literature shows that, the new algorithm developed is computationally MAC efficient. These results are useful for MDCT domain audio processing such as reverb synthesis, without having to reconstruct the time domain signal and then perform the necessary filtering operations. In audio coding, the psychoacoustic model plays a crucial role and is used to estimate the masking thresholds for adaptive bit-allocation. Transparent quality audio coding is possible if the quantization noise is kept below the masking threshold for each frame. In the existing methods, the masking threshold is calculated using the DFT of the signal frame separately for MDCT domain adaptive quantization. We have extended the spectral integration based psychoacoustic model proposed for sinusoidal modeling of audio signals to the MDCT domain. This has been possible because of the detailed analysis of the relation between DFT and MDCT; we interpret the MDCT coefficients as co-sinusoids and then apply the sinusoidal masking model. The validity of the masking threshold so derived is verified through listening tests as well as objective measures. Parametric coding techniques are used for low bit rate encoding of multi-channel audio such as 5.1 format surround audio. In these techniques, the surround channels are synthesized at the receiver using the analysis parameters of the parametric model. We develop algorithms for MDCT domain analysis and synthesis of reverberation. Integrating these ideas, a parametric audio coder is developed in the MDCT domain. For the parameter estimation, we use a novel analysis by synthesis scheme in the MDCT domain which results in better modeling of the spatial audio. The resulting parametric stereo coder is able to synthesize acceptable quality stereo audio from the mono audio channel and a side information of approximately 11 kbps. Further, an experimental audio coder is developed in the MDCT domain incorporating the new psychoacoustic model and the parametric model.

Many scientific data sets are contaminated by noise, either because of data acquisition process, or because of naturally occurring phenomena. A first step in analyzing such data sets is denoising, i.e., removing additive noise from a noisy image. For images, noise suppression is a delicate and a difficult task. A trade of between noise reduction and the preservation of actual image features has to be made in a way that enhances the relevant image content. The beginning chapter in this thesis is introductory in nature and discusses the Popular denoising techniques in spatial and frequency domains. Wavelet transform has wide applications in image processing especially in denoising of images. Wavelet systems are a set of building blocks that represent a signal in an expansion set involving indices for time and scale. These systems allow the multi-resolution representation of signals. Several well known denoising algorithms exist in wavelet domain which penalize the noisy coefficients by threshold them. We discuss the wavelet transform based denoising of images using bit planes. This approach preserves the edges in an image. The proposed approach relies on the fact that wavelet transform allows the denoising strategy to adapt itself according to directional features of coefficients in respective sub-bands. Further, issues related to low complexity implementation of this algorithm are discussed. The proposed approach has been tested on different sets images under different noise intensities. Studies have shown that this approach provides a significant reduction in normalized mean square error (NMSE). The denoised images are visually pleasing. Many of the image compression techniques still use the redundancy reduction property of the discrete cosine transform (DCT). So, the development of a denoising algorithm in DCT domain has a practical significance. In chapter 3, a DCT based denoising algorithm is presented. In general, the design of filters largely depends on the a-priori knowledge about the type of noise corrupting the image and image features. This makes the standard filters to be application and image specific. The most popular filters such as average, Gaussian and Wiener reduce noisy artifacts by smoothing. However, this operation normally results in smoothing of the edges as well. On the other hand, sharpening filters enhance the high frequency details making the image non-smooth. An integrated approach to design filters based on DCT is proposed in chapter 3. This algorithm reorganizes DCT coefficients in a wavelet transform manner to get the better energy clustering at desired spatial locations. An adaptive threshold is chosen because such adaptively can improve the wavelet threshold performance as it allows additional local information of the image to be incorporated in the algorithm. Evaluation results show that the proposed filter is robust under various noise distributions and does not require any a-priori Knowledge about the image. Inpainting is another application that comes under the category of image processing. In painting provides a way for reconstruction of small damaged portions of an image. Filling-in missing data in digital images has a number of applications such as, image coding and wireless image transmission for recovering lost blocks, special effects (e.g., removal of objects) and image restoration (e.g., removal of solid lines, scratches and noise removal). In chapter 4, a wavelet based in painting algorithm is presented for reconstruction of small missing and damaged portion of an image while preserving the overall image quality. This approach exploits the directional features that exist in wavelet coefficients in respective sub-bands. The concluding chapter presents a brief review of the three new approaches: wavelet and DCT based denoising schemes and wavelet based inpainting method.

Extracting speaker-specific information from speech is of great interest to both researchers and developers alike, since speaker recognition technology finds application in a wide range of areas, primary among them being forensics and biometric security systems. Several models and techniques have been employed to extract speaker information from the speech signal. Speech production is generally modeled as an excitation source followed by a filter. Physiologically, the source corresponds to the vocal fold vibrations and the filter corresponds to the spectrum-shaping vocal tract. Vocal tract-based features like the melfrequency cepstral coefficients (MFCCs) and linear prediction cepstral coefficients have been shown to contain speaker information. However, high speed videos of the larynx show that the vocal folds of different individuals vibrate differently. Voice source (VS)-based features have also been shown to perform well in speaker recognition tasks, thereby revealing that the VS does contain speaker information. Moreover, a combination of the vocal tract and VS-based features has been shown to give an improved performance, showing that the latter contains supplementary speaker information. In this study, the focus is on extracting speaker information from the VS. The existing techniques for the same are reviewed, and it is observed that the features which are obtained by fitting a time-domain model on the VS perform poorly than those obtained by simple transformations of the VS. Here, an attempt is made to propose an alternate way of characterizing the VS to extract speaker information, and to study the merits and shortcomings of the proposed speaker-specific features. The VS cannot be measured directly. Thus, to characterize the VS, we first need an estimate of the VS, and the integrated linear prediction residual (ILPR) extracted from the speech signal is used as the VS estimate in this study. The voice source linear prediction model, which was proposed in an earlier study to obtain the ILPR, is used in this work. It is hypothesized here that a speaker’s voice may be characterized by the relative proportions of the harmonics present in the VS. The pitch synchronous discrete cosine transform (DCT) is shown to capture these, and the gross shape of the ILPR in a few coefficients. The ILPR and hence its DCT coefficients are visually observed to distinguish between speakers. However, it is also observed that they do have intra-speaker variability, and thus it is hypothesized that the distribution of the DCT coefficients may capture speaker information, and this distribution is modeled by a Gaussian mixture model (GMM). The DCT coefficients of the ILPR (termed the DCTILPR) are directly used as a feature vector in speaker identification (SID) tasks. Issues related to the GMM, like the type of covariance matrix, are studied, and it is found that diagonal covariance matrices perform better than full covariance matrices. Thus, mixtures of Gaussians having diagonal covariances are used as speaker models, and by conducting SID experiments on three standard databases, it is found that the proposed DCTILPR features fare comparably with the existing VS-based features. It is also found that the gross shape of the VS contains most of the speaker information, and the very fine structure of the VS does not help in distinguishing speakers, and instead leads to more confusion between speakers. The major drawbacks of the DCTILPR are the session and handset variability, but they are also present in existing state-of-the-art speaker-specific VS-based features and the MFCCs, and hence seem to be common problems. There are techniques to compensate these variabilities, which need to be used when the systems using these features are deployed in an actual application. The DCTILPR is found to improve the SID accuracy of a system trained with MFCC features by 12%, indicating that the DCTILPR features capture speaker information which is missed by the MFCCs. It is also found that a combination of MFCC and DCTILPR features on a speaker verification task gives significant performance improvement in the case of short test utterances. Thus, on the whole, this study proposes an alternate way of extracting speaker information from the VS, and adds to the evidence for speaker information present in the VS.

No
As existing video processing technology is primarily developed in the pixel domain yet digital video is stored in compressed format, any application of those techniques to compressed videos would require decompression. For discrete cosine transform (DCT)-based MPEG compressed videos, the computing cost of standard row-by-row and column-by-column inverse DCT (IDCT) transforms for a block of 8 8 elements requires 4096 multiplications and 4032 additions, although practical implementation only requires 1024 multiplications and 896 additions. In this paper, we propose a new algorithm to extract videos directly from MPEG compressed domain (DCT domain) without full IDCT, which is described in three extraction schemes: 1) video extraction in 2 2 blocks with four coefficients; 2) video extraction in 4 4 blocks with four DCT coefficients; and 3) video extraction in 4 4 blocks with nine DCT coefficients. The computing cost incurred only requires 8 additions and no multiplication for the first scheme, 2 multiplication and 28 additions for the second scheme, and 47 additions (no multiplication) for the third scheme. Extensive experiments were carried out, and the results reveal that: 1) the extracted video maintains competitive quality in terms of visual perception and inspection and 2) the extracted videos preserve the content well in comparison with those fully decompressed ones in terms of histogram measurement. As a result, the proposed algorithm will provide useful tools in bridging the gap between pixel domain and compressed domain to facilitate content analysis with low latency and high efficiency such as those applications in surveillance videos, interactive multimedia, and image processing.

L'athérosclérose est une maladie vasculaire complexe qui affecte la paroi des artères (par l'épaississement) et les lumières (par la formation de plaques). La rupture d'une plaque de l'artère carotide peut également provoquer un accident vasculaire cérébral ischémique et des complications. Bien que plusieurs modalités d'imagerie médicale soient actuellement utilisées pour évaluer la stabilité d'une plaque, elles présentent des limitations telles que l'irradiation, les propriétés invasives, une faible disponibilité clinique et un coût élevé. L'échographie est une méthode d'imagerie sûre qui permet une analyse en temps réel pour l'évaluation des tissus biologiques. Il est intéressant et prometteur d’appliquer une échographie vasculaire pour le dépistage et le diagnostic précoces des plaques d’artère carotide. Cependant, les ultrasons vasculaires actuels identifient uniquement la morphologie d'une plaque en termes de luminosité d'écho ou l’impact de cette plaque sur les caractéristiques de l’écoulement sanguin, ce qui peut ne pas être suffisant pour diagnostiquer l’importance de la plaque. La technique d’élastographie vasculaire non-intrusive (« noninvasive vascular elastography (NIVE) ») a montré le potentiel de détermination de la stabilité d'une plaque. NIVE peut déterminer le champ de déformation de la paroi vasculaire en mouvement d’une artère carotide provoqué par la pulsation cardiaque naturelle. En raison des différences de module de Young entre les différents tissus des vaisseaux, différents composants d’une plaque devraient présenter différentes déformations, caractérisant ainsi la stabilité de la plaque. Actuellement, les performances et l’efficacité numérique sous-optimales limitent l’acceptation clinique de NIVE en tant que méthode rapide et efficace pour le diagnostic précoce des plaques vulnérables. Par conséquent, il est nécessaire de développer NIVE en tant qu’outil d’imagerie non invasif, rapide et économique afin de mieux caractériser la vulnérabilité liée à la plaque. La procédure à suivre pour effectuer l’analyse NIVE consiste en des étapes de formation et de post-traitement d’images. Cette thèse vise à améliorer systématiquement la précision de ces deux aspects de NIVE afin de faciliter la prédiction de la vulnérabilité de la plaque carotidienne. Le premier effort de cette thèse a été dédié à la formation d'images (Chapitre 5). L'imagerie par oscillations transversales a été introduite dans NIVE. Les performances de l’imagerie par oscillations transversales couplées à deux estimateurs de contrainte fondés sur un modèle de déformation fine, soit l’ « affine phase-based estimator (APBE) » et le « Lagrangian speckle model estimator (LSME) », ont été évaluées. Pour toutes les études de simulation et in vitro de ce travail, le LSME sans imagerie par oscillation transversale a surperformé par rapport à l'APBE avec imagerie par oscillations transversales. Néanmoins, des estimations de contrainte principales comparables ou meilleures pourraient être obtenues avec le LSME en utilisant une imagerie par oscillations transversales dans le cas de structures tissulaires complexes et hétérogènes. Lors de l'acquisition de signaux ultrasonores pour la formation d'images, des mouvements hors du plan perpendiculaire au plan de balayage bidimensionnel (2-D) existent. Le deuxième objectif de cette thèse était d'évaluer l'influence des mouvements hors plan sur les performances du NIVE 2-D (Chapitre 6). À cette fin, nous avons conçu un dispositif expérimental in vitro permettant de simuler des mouvements hors plan de 1 mm, 2 mm et 3 mm. Les résultats in vitro ont montré plus d'artefacts d'estimation de contrainte pour le LSME avec des amplitudes croissantes de mouvements hors du plan principal de l’image. Malgré tout, nous avons néanmoins obtenu des estimations de déformations robustes avec un mouvement hors plan de 2.0 mm (coefficients de corrélation supérieurs à 0.85). Pour un jeu de données cliniques de 18 participants présentant une sténose de l'artère carotide, nous avons proposé d'utiliser deux jeux de données d'analyses sur la même plaque carotidienne, soit des images transversales et longitudinales, afin de déduire les mouvements hors plan (qui se sont avérés de 0.25 mm à 1.04 mm). Les résultats cliniques ont montré que les estimations de déformations restaient reproductibles pour toutes les amplitudes de mouvement, puisque les coefficients de corrélation inter-images étaient supérieurs à 0.70 et que les corrélations croisées normalisées entre les images radiofréquences étaient supérieures à 0.93, ce qui a permis de démontrer une plus grande confiance lors de l'analyse de jeu de données cliniques de plaques carotides à l'aide du LSME. Enfin, en ce qui concerne le post-traitement des images, les algorithmes NIVE doivent estimer les déformations des parois des vaisseaux à partir d’images reconstituées dans le but d’identifier les tissus mous et durs. Ainsi, le dernier objectif de cette thèse était de développer un algorithme d'estimation de contrainte avec une résolution de la taille d’un pixel ainsi qu'une efficacité de calcul élevée pour l'amélioration de la précision de NIVE (Chapitre 7). Nous avons proposé un estimateur de déformation de modèle fragmenté (SMSE) avec lequel le champ de déformation dense est paramétré avec des descriptions de transformées en cosinus discret, générant ainsi des composantes de déformations affines (déformations axiales et latérales et en cisaillement) sans opération mathématique de dérivées. En comparant avec le LSME, le SMSE a réduit les erreurs d'estimation lors des tests de simulations, ainsi que pour les mesures in vitro et in vivo. De plus, la faible mise en oeuvre de la méthode SMSE réduit de 4 à 25 fois le temps de traitement par rapport à la méthode LSME pour les simulations, les études in vitro et in vivo, ce qui pourrait permettre une implémentation possible de NIVE en temps réel.
Atherosclerosis is a complex vascular disease that affects artery walls (by thickening) and lumens (by plaque formation). The rupture of a carotid artery plaque may also induce ischemic stroke and complications. Despite the use of several medical imaging modalities to evaluate the stability of a plaque, they present limitations such as irradiation, invasive property, low clinical availability and high cost. Ultrasound is a safe imaging method with a real time capability for assessment of biological tissues. It is clinically used for early screening and diagnosis of carotid artery plaques. However, current vascular ultrasound technologies only identify the morphology of a plaque in terms of echo brightness or the impact of the vessel narrowing on flow properties, which may not be sufficient for optimum diagnosis. Noninvasive vascular elastography (NIVE) has been shown of interest for determining the stability of a plaque. Specifically, NIVE can determine the strain field of the moving vessel wall of a carotid artery caused by the natural cardiac pulsation. Due to Young’s modulus differences among different vessel tissues, different components of a plaque can be detected as they present different strains thereby potentially helping in characterizing the plaque stability. Currently, sub-optimum performance and computational efficiency limit the clinical acceptance of NIVE as a fast and efficient method for the early diagnosis of vulnerable plaques. Therefore, there is a need to further develop NIVE as a non-invasive, fast and low computational cost imaging tool to better characterize the plaque vulnerability. The procedure to perform NIVE analysis consists in image formation and image post-processing steps. This thesis aimed to systematically improve the accuracy of these two aspects of NIVE to facilitate predicting carotid plaque vulnerability. The first effort of this thesis has been targeted on improving the image formation (Chapter 5). Transverse oscillation beamforming was introduced into NIVE. The performance of transverse oscillation imaging coupled with two model-based strain estimators, the affine phase-based estimator (APBE) and the Lagrangian speckle model estimator (LSME), were evaluated. For all simulations and in vitro studies, the LSME without transverse oscillation imaging outperformed the APBE with transverse oscillation imaging. Nonetheless, comparable or better principal strain estimates could be obtained with the LSME using transverse oscillation imaging in the case of complex and heterogeneous tissue structures. During the acquisition of ultrasound signals for image formation, out-of-plane motions which are perpendicular to the two-dimensional (2-D) scan plane are existing. The second objective of this thesis was to evaluate the influence of out-of-plane motions on the performance of 2-D NIVE (Chapter 6). For this purpose, we designed an in vitro experimental setup to simulate out-of-plane motions of 1 mm, 2 mm and 3 mm. The in vitro results showed more strain estimation artifacts for the LSME with increasing magnitudes of out-of-plane motions. Even so, robust strain estimations were nevertheless obtained with 2.0 mm out-of-plane motion (correlation coefficients higher than 0.85). For a clinical dataset of 18 participants with carotid artery stenosis, we proposed to use two datasets of scans on the same carotid plaque, one cross-sectional and the other in a longitudinal view, to deduce the out-of-plane motions (estimated to be ranging from 0.25 mm to 1.04 mm). Clinical results showed that strain estimations remained reproducible for all motion magnitudes since inter-frame correlation coefficients were higher than 0.70, and normalized cross-correlations between radiofrequency images were above 0.93, which indicated that confident motion estimations can be obtained when analyzing clinical dataset of carotid plaques using the LSME. Finally, regarding the image post-processing component of NIVE algorithms to estimate strains of vessel walls from reconstructed images with the objective of identifying soft and hard tissues, we developed a strain estimation method with a pixel-wise resolution as well as a high computation efficiency for improving NIVE (Chapter 7). We proposed a sparse model strain estimator (SMSE) for which the dense strain field is parameterized with Discrete Cosine Transform descriptions, thereby deriving affine strain components (axial and lateral strains and shears) without mathematical derivative operations. Compared with the LSME, the SMSE reduced estimation errors in simulations, in vitro and in vivo tests. Moreover, the sparse implementation of the SMSE reduced the processing time by a factor of 4 to 25 compared with the LSME based on simulations, in vitro and in vivo results, which is suggesting a possible implementation of NIVE in real time.