Esta dissertação apresenta o desenvolvimento de arquiteturas para a compressão JPEG, onde são apresentadas arquiteturas de um compressor JPEG para imagens em tons de cinza, de um compressor JPEG para imagens coloridas e de um conversor de espaço de cores de RGB para YCbCr. As arquiteturas desenvolvidas são detalhadamente apresentadas, tendo sido completamente descritas em VHDL, com sua síntese direcionada para FPGAs da família Flex10KE da Altera. A arquitetura integrada do compressor JPEG para imagens em tons de cinza possui uma latência mínima de 237 ciclos de clock e processa uma imagem de 640x480 pixels em 18,5ms, permitindo uma taxa de processamento de 54 imagens por segundo. As estimativas realizadas em torno da taxa de compressão obtida indicam que ela seria de aproximadamente 6,2 vezes ou de 84 %. A arquitetura integrada do compressor JPEG para imagens coloridas foi gerada a partir de adaptações na arquitetura do compressor para imagens em tons de cinza. Esta arquitetura também possui a latência mínima de 237 ciclos de clock, sendo capaz de processar uma imagem coloria de 640 x 480 pixels em 54,4ms, permitindo uma taxa de processamento de 18,4 imagens por segundo. A taxa de compressão obtida, segundo estimativas, seria de aproximadamente 14,4 vezes ou de 93 %. A arquitetura para o conversor de espaço de cores de RBG para YCbCr possui uma latência de 6 ciclos de clock e é capaz de processar uma imagem colorida de 640x480 pixels em 84,6ms, o que permite uma taxa de processamento de 11,8 imagens por segundo. Esta arquitetura não chegou a ser integrada com a arquitetura do compressor de imagens coloridas, mas algumas sugestões e estimativas foram realizadas nesta direção. / This dissertation presents the design of architectures for JPEG image compression. Architectures for a gray scale images JPEG compressor that were developed are herein presented. This work also addresses a color images JPEG compressor and a color space converter. The designed architectures are described in detail and they were completely described in VHDL, with synthesis directed for Altera Flex10KE family of FPGAs. The integrated architecture for gray scale images JPEG compressor has a minimum latency of 237 clock cycles and it processes an image of 640x480 pixels in 18,5ms, allowing a processing rate of 54 images per second. The compression rate, according to estimates, would be of 6,2 times or 84%, in percentage of bits compression. The integrated architecture for color images JPEG compression was generated starting from incremental changes in the architecture of gray scale images compressor. This architecture also has the minimum latency of 237 clock cycles and it can process a color image of 640 x 480 pixels in 54,4ms, allowing a processing rate of 18,4 images per second. The compression rate, according to estimates, would be of 14,4 times or 93%, in percentage of bits compression. The architecture for space color conversor from RBG to YCbCr has a latency of 6 clock cycles and it is able to process a color image of 640 x 480 pixels in 84,6ms, allowing a processing rate of 11,8 images per second. This architecture was finally not integrated with the color images compressor architecture, but some suggestions, alternatives and estimates were made in this direction.

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published_or_final_version / abstract / Electrical and Electronic Engineering / Master / Master of Philosophy

Image sizes have increased exponentially in recent years. The resulting high-resolution images are typically encoded in a lossy fashion to achieve high compression ratios. Lossy compression can be categorized into visually lossless and visually lossy compression depending on the visibility of compression artifacts. This dissertation proposes visually lossless coding methods as well as a visually lossy coding method with perceptual quality control. All resulting codestreams are JPEG2000 Part-I compliant.Visually lossless coding is increasingly considered as an alternative to numerically lossless coding. In order to hide compression artifacts caused by quantization, visibility thresholds (VTs) are measured and used for quantization of subbands in JPEG2000. In this work, VTs are experimentally determined from statistically modeled quantization distortion, which is based on the distribution of wavelet coefficients and the dead-zone quantizer of JPEG2000. The resulting VTs are adjusted for locally changing background through a visual masking model, and then used to determine the minimum number of coding passes to be included in a codestream for visually lossless quality under desired viewing conditions. The proposed coding scheme successfully yields visually lossless images at competitive bitrates compared to those of numerically lossless coding and visually lossless algorithms in the literature.This dissertation also investigates changes in VTs as a function of display resolution and proposes a method which effectively incorporates multiple VTs for various display resolutions into the JPEG2000 framework. The proposed coding method allows for visually lossless decoding at resolutions natively supported by the wavelet transform as well as arbitrary intermediate resolutions, using only a fraction of the full-resolution codestream. When images are browsed remotely, this method can significantly reduce bandwidth usage.Contrary to images encoded in the visually lossless manner, highly compressed images inevitably have visible compression artifacts. To minimize these artifacts, many compression algorithms exploit the varying sensitivity of the human visual system (HVS) to different frequencies, which is typically obtained at the near-threshold level where distortion is just noticeable. However, it is unclear that the same frequency sensitivity applies at the supra-threshold level where distortion is highly visible. In this dissertation, the sensitivity of the HVS for several supra-threshold distortion levels is measured based on the JPEG2000 quantization distortion model. Then, a low-complexity JPEG2000 encoder using the measured sensitivity is described. The proposed visually lossy encoder significantly reduces encoding time while maintaining superior visual quality compared with conventional JPEG2000 encoders.

by Lam Chi Wah. / Thesis submitted in: December 1997. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1998. / Includes bibliographical references (leaves 89-91). / Abstract also in Chinese. / Chapter Chapter 1 --- Introduction to Data Compression and Image Coding --- p.1 / Chapter 1.1 --- Introduction --- p.1 / Chapter 1.2 --- Fundamental Principle of Data Compression --- p.2 / Chapter 1.3 --- Some Data Compression Algorithms --- p.3 / Chapter 1.4 --- Image Coding Overview --- p.4 / Chapter 1.5 --- Image Transformation --- p.5 / Chapter 1.6 --- Quantization --- p.7 / Chapter 1.7 --- Lossless Coding --- p.8 / Chapter Chapter 2 --- Subband Coding and Wavelet Transform --- p.9 / Chapter 2.1 --- Subband Coding Principle --- p.9 / Chapter 2.2 --- Perfect Reconstruction --- p.11 / Chapter 2.3 --- Multi-Channel System --- p.13 / Chapter 2.4 --- Discrete Wavelet Transform --- p.13 / Chapter Chapter 3 --- Vector Quantization (VQ) --- p.16 / Chapter 3.1 --- Introduction --- p.16 / Chapter 3.2 --- Basic Vector Quantization Procedure --- p.17 / Chapter 3.3 --- Codebook Searching and the LBG Algorithm --- p.18 / Chapter 3.3.1 --- Codebook --- p.18 / Chapter 3.3.2 --- LBG Algorithm --- p.19 / Chapter 3.4 --- Problem of VQ and Variations of VQ --- p.21 / Chapter 3.4.1 --- Classified VQ (CVQ) --- p.22 / Chapter 3.4.2 --- Finite State VQ (FSVQ) --- p.23 / Chapter 3.5 --- Vector Quantization on Wavelet Coefficients --- p.24 / Chapter Chapter 4 --- Vector Wavelet Transform-Linear Predictor Coding --- p.26 / Chapter 4.1 --- Image Coding Using Wavelet Transform with Vector Quantization --- p.26 / Chapter 4.1.1 --- Future Standard --- p.26 / Chapter 4.1.2 --- Drawback of DCT --- p.27 / Chapter 4.1.3 --- "Wavelet Coding and VQ, the Future Trend" --- p.28 / Chapter 4.2 --- Mismatch between Scalar Transformation and VQ --- p.29 / Chapter 4.3 --- Vector Wavelet Transform (VWT) --- p.30 / Chapter 4.4 --- Example of Vector Wavelet Transform --- p.34 / Chapter 4.5 --- Vector Wavelet Transform - Linear Predictive Coding (VWT-LPC) --- p.36 / Chapter 4.6 --- An Example of VWT-LPC --- p.38 / Chapter Chapter 5 --- Vector Quantizaton with Inter-band Bit Allocation (IBBA) --- p.40 / Chapter 5.1 --- Bit Allocation Problem --- p.40 / Chapter 5.2 --- Bit Allocation for Wavelet Subband Vector Quantizer --- p.42 / Chapter 5.2.1 --- Multiple Codebooks --- p.42 / Chapter 5.2.2 --- Inter-band Bit Allocation (IBBA) --- p.42 / Chapter Chapter 6 --- Parental Finite State Vector Quantizers (PFSVQ) --- p.45 / Chapter 6.1 --- Introduction --- p.45 / Chapter 6.2 --- Parent-Child Relationship Between Subbands --- p.46 / Chapter 6.3 --- Wavelet Subband Vector Structures for VQ --- p.48 / Chapter 6.3.1 --- VQ on Separate Bands --- p.48 / Chapter 6.3.2 --- InterBand Information for Intraband Vectors --- p.49 / Chapter 6.3.3 --- Cross band Vector Methods --- p.50 / Chapter 6.4 --- Parental Finite State Vector Quantization Algorithms --- p.52 / Chapter 6.4.1 --- Scheme I: Parental Finite State VQ with Parent Index Equals Child Class Number --- p.52 / Chapter 6.4.2 --- Scheme II: Parental Finite State VQ with Parent Index Larger than Child Class Number --- p.55 / Chapter Chapter 7 --- Simulation Result --- p.58 / Chapter 7.1 --- Introduction --- p.58 / Chapter 7.2 --- Simulation Result of Vector Wavelet Transform (VWT) --- p.59 / Chapter 7.3 --- Simulation Result of Vector Wavelet Transform - Linear Predictive Coding (VWT-LPC) --- p.61 / Chapter 7.3.1 --- First Test --- p.61 / Chapter 7.3.2 --- Second Test --- p.61 / Chapter 7.3.3 --- Third Test --- p.61 / Chapter 7.4 --- Simulation Result of Vector Quantization Using Inter-band Bit Allocation (IBBA) --- p.62 / Chapter 7.5 --- Simulation Result of Parental Finite State Vector Quantizers (PFSVQ) --- p.63 / Chapter Chapter 8 --- Conclusion --- p.86 / REFERENCE --- p.89

by Man-Ching Auyeung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1997. / Includes bibliographical references (leaves 86-93). / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Transform coding and the JPEG scheme --- p.2 / Chapter 1.2 --- Motivation --- p.5 / Chapter 1.3 --- Thesis outline --- p.6 / Chapter 2 --- MED and DC Coefficient Restoration scheme --- p.8 / Chapter 2.1 --- Introduction --- p.8 / Chapter 2.2 --- MED and DC Coefficient Restoration scheme --- p.10 / Chapter 2.2.1 --- Definition --- p.10 / Chapter 2.2.2 --- Existing schemes --- p.11 / Chapter 2.3 --- DC Coefficient Restoration scheme using block selection scheme --- p.14 / Chapter 2.4 --- Joint optimization technique --- p.16 / Chapter 2.4.1 --- Lagrange multiplier method --- p.17 / Chapter 2.4.2 --- Algorithm description --- p.18 / Chapter 2.5 --- Experimental results --- p.20 / Chapter 2.6 --- Summary --- p.32 / Chapter 3 --- Low Frequency Walsh Transform Coefficient Restoration scheme --- p.34 / Chapter 3.1 --- Introduction --- p.34 / Chapter 3.2 --- Restoration of low frequency coefficient using Walsh transform --- p.35 / Chapter 3.3 --- Selection of quantization table optimized for Walsh transform --- p.37 / Chapter 3.3.1 --- Image model used --- p.39 / Chapter 3.3.2 --- Infinite uniform quantization --- p.40 / Chapter 3.3.3 --- Search for an optimized quantization matrix --- p.42 / Chapter 3.4 --- Walsh transform-based LFCR scheme --- p.44 / Chapter 3.5 --- Experimental results --- p.46 / Chapter 3.6 --- Summary --- p.56 / Chapter 4 --- Low Frequency DCT Coefficient Prediction --- p.57 / Chapter 4.1 --- Introduction --- p.57 / Chapter 4.2 --- Low Frequency Coefficient Prediction scheme with negligible side information --- p.58 / Chapter 4.2.1 --- Selection of threshold --- p.63 / Chapter 4.2.2 --- Representation of the AC component --- p.63 / Chapter 4.3 --- Experimental results --- p.67 / Chapter 4.4 --- Summary --- p.84 / Chapter 5 --- Conclusions --- p.86 / Appendix A --- p.89 / Bibliography --- p.90

by Tse, Fu Wing. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1996. / Includes bibliographical references (leaves 155-[63]). / Acknowledgment --- p.iii / Abstract --- p.iv / Contents --- p.vi / List of Tables --- p.x / List of Figures --- p.xii / Notations --- p.xvii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- DC coefficient restoration --- p.1 / Chapter 1.2 --- Model based image compression --- p.5 / Chapter 1.3 --- The minimum edge difference criterion and the existing estima- tion schemes --- p.7 / Chapter 1.3.1 --- Fundamental definitions --- p.8 / Chapter 1.3.2 --- The minimum edge difference criterion --- p.9 / Chapter 1.3.3 --- The existing estimation schemes --- p.10 / Chapter 1.4 --- Thesis outline --- p.14 / Chapter 2 --- A mathematical description of the DC coefficient restoration problem --- p.17 / Chapter 2.1 --- Introduction --- p.17 / Chapter 2.2 --- Mathematical formulation --- p.18 / Chapter 2.3 --- Properties of H --- p.22 / Chapter 2.4 --- Analysis of the DC coefficient restoration problem --- p.22 / Chapter 2.5 --- The MED criterion as an image model --- p.25 / Chapter 2.6 --- Summary --- p.27 / Chapter 3 --- The global estimation scheme --- p.29 / Chapter 3.1 --- Introduction --- p.29 / Chapter 3.2 --- the global estimation scheme --- p.30 / Chapter 3.3 --- Theory of successive over-relaxation --- p.34 / Chapter 3.3.1 --- Introduction --- p.34 / Chapter 3.3.2 --- Gauss-Seidel iteration --- p.35 / Chapter 3.3.3 --- Theory of successive over-relaxation --- p.38 / Chapter 3.3.4 --- Estimation of optimal relaxation parameter --- p.41 / Chapter 3.4 --- Using successive over-relaxation in the global estimation scheme --- p.43 / Chapter 3.5 --- Experiments --- p.48 / Chapter 3.6 --- Summary --- p.49 / Chapter 4 --- The block selection scheme --- p.52 / Chapter 4.1 --- Introduction --- p.52 / Chapter 4.2 --- Failure of the minimum edge difference criterion --- p.53 / Chapter 4.3 --- The block selection scheme --- p.55 / Chapter 4.4 --- Using successive over-relaxation with the block selection scheme --- p.57 / Chapter 4.5 --- Practical considerations --- p.58 / Chapter 4.6 --- Experiments --- p.60 / Chapter 4.7 --- Summary --- p.61 / Chapter 5 --- The edge selection scheme --- p.65 / Chapter 5.1 --- Introduction --- p.65 / Chapter 5.2 --- Edge information and the MED criterion --- p.66 / Chapter 5.3 --- Mathematical formulation --- p.70 / Chapter 5.4 --- Practical Considerations --- p.74 / Chapter 5.5 --- Experiments --- p.76 / Chapter 5.6 --- Discussion of edge selection scheme --- p.78 / Chapter 5.7 --- Summary --- p.79 / Chapter 6 --- Performance Analysis --- p.81 / Chapter 6.1 --- Introduction --- p.81 / Chapter 6.2 --- Mathematical derivations --- p.82 / Chapter 6.3 --- Simulation results --- p.92 / Chapter 6.4 --- Summary --- p.96 / Chapter 7 --- The DC coefficient restoration scheme with baseline JPEG --- p.97 / Chapter 7.1 --- Introduction --- p.97 / Chapter 7.2 --- General specifications --- p.97 / Chapter 7.3 --- Simulation results --- p.101 / Chapter 7.3.1 --- The global estimation scheme with the block selection scheme --- p.101 / Chapter 7.3.2 --- The global estimation scheme with the edge selection scheme --- p.113 / Chapter 7.3.3 --- Performance comparison at the same bit rate --- p.121 / Chapter 7.4 --- Computation overhead using the DC coefficient restoration scheme --- p.134 / Chapter 7.5 --- Summary --- p.134 / Chapter 8 --- Conclusions and Discussions --- p.136 / Chapter A --- Fundamental definitions --- p.144 / Chapter B --- Irreducibility by associated directed graph --- p.146 / Chapter B.1 --- Irreducibility and associated directed graph --- p.146 / Chapter B.2 --- Derivation of irreducibility --- p.147 / Chapter B.3 --- Multiple blocks selection --- p.149 / Chapter B.4 --- Irreducibility with edge selection --- p.151 / Chapter C --- Sample images --- p.153 / Bibliography --- p.155

The rapid growth of wireless communication and widespread access to information has resulted in a strong demand for robust transmission of compressed images over wireless channels. The challenge of robust transmission is to protect the compressed image data against loss, in such a way as to maximize the received image quality. This thesis addresses this problem and provides an investigation of a forward error correction (FEC) technique that has been evaluated in the context of the emerging JPEG2000 standard. Not much effort has been made in the JPEG2000 project regarding error resilience. The only techniques standardized are based on insertion of marker codes in the code-stream, which may be used to restore high-level synchronization between the decoder and the code-stream. This helps to localize error and prevent it from propagating through the entire code-stream. Once synchronization is achieved, additional tools aim to exploit as much of the remaining data as possible. Although these techniques help, they cannot recover lost data. FEC adds redundancy into the bit-stream, in exchange for increased robustness to errors. We investigate unequal protection schemes for JPEG2000 by applying different levels of protection to different quality layers in the code-stream. More particularly, the results reported in this thesis provide guidance concerning the selection of JPEG2000 coding parameters and appropriate combinations of Reed-Solomon (RS) codes for typical wireless bit error rates. We find that unequal protection schemes together with the use of resynchronization makers and some additional tools can significantly improve the image quality in deteriorating channel conditions. The proposed channel coding scheme is easily incorporated into the existing JPEG2000 code-stream structure and experimental results clearly demonstrate the viability of our approach

<p>In this Master Thesis, a model of a video coding system that uses the transportation plan taken from the calculation of the Kantorovich distance is developed. The coder uses the transportation plan instead of the differential image and sends it through blocks of transformation, quantization and coding. </p><p>The Kantorovich distance is a rather unknown distance metric that is used in optimization theory but is also applicable on images. It can be defined as the cheapest way to transport the mass of one image into another and the cost is determined by the distance function chosen to measure distance between pixels. The transportation plan is a set of finitely many five-dimensional vectors that show exactly how the mass should be moved from the transmitting pixel to the receiving pixel in order to achieve the Kantorovich distance between the images. A vector in the transportation plan is called an arc. </p><p>The original transportation plan was transformed into a new set of four-dimensional vectors called the modified difference plan. This set replaces the transmitting pixel and the receiving pixel with the distance from the transmitting pixel of the last arc and the relative distance between the receiving pixel and the transmitting pixel. The arcs where the receiving pixels are the same as the transmitting pixels are redundant and were removed. The coder completed an eleven frame sequence of size 128x128 pixels in eight to ten hours.</p>