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Ultra-High-Throughput VLSI Architecture of H.265/HEVC CABAC Encoder for UHDTV Applications

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2015年第3期25卷 497-507页

作者： Zhou, Dajiang Zhou, Jinjia Fei, Wei Goto, Satoshi Waseda Univ Grad Sch Informat Prod & Syst Kitakyushu Fukuoka 8080135 Japan

Ultra high definition television (UHDTV) imposes extremely high throughput requirement on video encoders based on High Efficiency Video coding (H.265/HEVC) and Advanced Video coding (H.264/AVC) standards. Context-adaptive binary arithmetic coding (CABAC) is the entropy coding component of these standards. In very-large-scale integration implementation, CABAC has known difficulties in being effectively pipelined and parallelized, due to the critical bin-to-bin data dependencies in its algorithm. This paper addresses the throughput requirement of CABAC encoding for UHDTV applications. The proposed optimizations including prenormalization, hybrid path coverage and lookahead rLPS to reduce the critical path delay of binary arithmetic encoding (BAE) by exploiting the incompleteness of data dependencies in rLPS updating. Meanwhile, the number of bins BAE delivers per clock cycle is increased by the proposed bypass bin splitting technique. The context modeling and binarization components are also optimized. As a result, our CABAC encoder delivers an average of 4.37 bins per clock cycle. Its maximum clock frequency reaches 420 MHz when synthesized in 90 nm. The corresponding overall throughput is 1836 Mbin/s that is 62.5% higher than the state-of-the-art architecture.

关键词： Advanced Video coding (AVC) context-adaptive binary arithmetic coding (CABAC) entropy coding H.264 H.265 High Efficiency Video coding (HEVC) Super Hi-Vision ultra high definition ultra high definition television (UHDTV) very-large-scale integration (VLSI) video encoder

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VARIABLE BIT RATE ADAPTIVE PREDICTIVE CODER

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 1992年第3期40卷 511-517页

作者： DEDES, IS VAMAN, DR CHAKRAVARTHY, CV STEVENS INST TECHNOL LIB CTR ISDNHOBOKENNJ 07030

An adaptive predictive coder providing almost toll quality at 16 kb/s and minimal degradation when the bit rate is lowered to 9.6 kb/s is described. The coder can operate at intermediate bit rates and can also change bit rate on a packet-by-packet basis. Variable bit rate operation is acheived through the use of switched quantization, thus eliminating the need for buffering of the output. A noise shaping filter provides a flexible control of the output noise spectrum. The noise shaping filter, in conjunction with an enhanced way to adapt the quantizer step size, which tries to accommodate the quantization noise feedback, account for the toll quality. By quantizing the residue with more than one quantizer, the effective number of bits per sample can be controlled in a deterministic way, regardless of the entropy of the residue. The lower limit of operation is at 9.6 kb/s. Performance of the coder under random bit errors is also presented. It has been found that only at error rates of 10(-2) and higher does the degradation becomes objectionable.

关键词： Bit rate Speech Noise shaping Delay Filters Interpolation Degradation Quantization Traffic control entropy coding

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Robust wireless image transmission based on turbo-coded OFDM

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IEEE TRANSACTIONS ON CONSUMER ELECTRONICS 2002年第3期48卷 724-731页

作者： Yang, J Lee, MH Jiang, MQ Park, JY Wuhan Univ Technol Wuhan 430070 Peoples R China Chonbuk Natl Univ Inst Inform & Comm Chonju South Korea Wuhan Univ Wuhan 430072 Peoples R China

In this paper a robust image transmission system incorporating perceptually-based coding and error protection is proposed for wireless channels. The perceptually-based image compression coder consists of a wavelet transform, adaptive quantization and variable-length entropy encoding. Uniform quantization, adaptive quantization were all computed for the wavelet transform and comparisons of the methods are presented The performance of adaptive quantization is superior to that of uniform quantization The quantization data are encoded using Turbo code. It is shown, through simulations, that wireless image transmission using turbo coder OFDM is better suited to a multipath channel than a, single carrier transmission technique.

关键词： OFDM modulation modulation coding turbo codes visual communication image coding transform coding quantisation (signal) discrete wavelet transforms multipath channels adaptive signal processing variable length codes entropy codes turbo-cod Orthogonal frequency division multiplexing Multipath channels transform coding uniform quantization adaptive signal processing Image communication systems image coding entropy coding adaptive quantization turbo codes discrete wavelet transform modulation coding variable length codes

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Efficient bilevel image compression by grouping symbols of chain coding techniques

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OPTICAL ENGINEERING 2009年第3期48卷 037001-1-037001-1页

作者： Alcaraz-Corona, Sergio Neri-Calderon, Ricardo A. Rodriguez-Dagnino, Ramon M. Ctr Elect & Telecommun Monterrey 64849 NL Mexico

We propose a procedure that can improve the coding efficiency of bilevel image compression schemes that are based on chain coding techniques and entropy coders. The two chain coding techniques analyzed in this study employ three and eight symbols, respectively, to code the outline of object shapes in bilevel images. Once we have the chain code representation of a contour, we group the original chain symbols in blocks of two or more symbols to build new extended alphabets from which we can obtain more efficient compression rates by using a statistical model that best represents our new alphabets and entropy coding. The coding efficiency of every new alphabet is measured by its entropy, average length in bits per original source symbol, and the total length in bits that represent the compressed image. We compare the compression efficiency between our two chain coding techniques using our three entropy coding parameters for symbol groupings of different sizes. In our experiments, we also show how our blocking approach produces an entropy value that is lower than its expected theoretical counterpart for a given order of symbol groupings and, as a consequence, the average and total lengths are expected to follow a decreasing pattern as well. Finally, we compare our best encoding model against the Joint Bilevel Image Experts Group's JBIG and JBIG2 bilevel image compression standards. (C) 2009 Society of Photo-Optical Instrumentation Engineers. [DOI: 10.1117/1.3099715]

关键词： Chain codes bilevel images entropy coding symbol groupings source extensions JBIG JBIG2

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Context modeling based lossless compression of radio-frequency data for software-based ultrasound beamforming

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BIOMEDICAL SIGNAL PROCESSING AND CONTROL 2013年第6期8卷 682-687页

作者： Lim, Chai-eun Kim, Gi-duck Yoon, Changhan Kim, Jung-jun Kim, Kang-sik Song, Tai-kyong Yoo, Yangmo Sogang Univ Dept Elect Engn Seoul 121742 South Korea Sogang Univ Sogang Inst Adv Technol Seoul 121742 South Korea Samsung Elect Suwon South Korea

A new lossless compression method using context modeling for ultrasound radio-frequency (RF) data is presented. In the proposed compression method, the combination of context modeling and entropy coding is used for effectively lowering the data transfer rates for modern software-based medical ultrasound imaging systems. From the phantom and in vivo data experiments, the proposed lossless compression method provides the average compression ratio of 0.45 compared to the Burg and JPEG-LS methods (0.52 and 0.55, respectively). This result indicates that the proposed compression method is capable of transferring 64-channel 40-MHz ultrasound RF data with a 16-lane PCI-Express 2.0 bus for software beamforming in real time. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Ultrasound beamforming Lossless compression Context modeling entropy coding

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Rate-distortion optimization for video compression

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IEEE SIGNAL PROCESSING MAGAZINE 1998年第6期15卷 74-90页

作者： Sullivan, GJ Wiegand, T PictureTel Corp Commun Core Res Andover MA USA Univ Erlangen Nurnberg D-8520 Erlangen Germany

The rate-distortion efficiency of video compression schemes is based on a sophisticated interaction between various motion representation possibilities, waveform coding of differences, and waveform coding of various refreshed regions. Hence, a key problem in high-compression video coding is the operational control of the encoder. This problem is compounded by the widely varying content and motion found in typical video sequences, necessitating the selection between different representation possibilities with varying rate-distortion efficiency. This article addresses the problem of video encoder optimization and discusses its consequences on the compression architecture of the overall coding system. Based on the well-known hybrid video coding structure, Lagrangian optimization techniques are presented that try to answer the question: what part of the video signal should be coded using what method and parameter settings?.

关键词： Rate-distortion Video compression Bit rate Video coding Quantization Switches Motion compensation Video codecs entropy coding ISO

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End-to-End Optimized Versatile Image Compression With Wavelet-Like Transform

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IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 2022年第3期44卷 1247-1263页

作者： Ma, Haichuan Liu, Dong Yan, Ning Li, Houqiang Wu, Feng Univ Sci & Technol China CAS Key Lab Technol Geospatial Informat Proc & Ap Hefei 230027 Peoples R China

Built on deep networks, end-to-end optimized image compression has made impressive progress in the past few years. Previous studies usually adopt a compressive auto-encoder, where the encoder part first converts image into latent features, and then quantizes the features before encoding them into bits. Both the conversion and the quantization incur information loss, resulting in a difficulty to optimally achieve arbitrary compression ratio. We propose iWave++ as a new end-to-end optimized image compression scheme, in which iWave, a trained wavelet-like transform, converts images into coefficients without any information loss. Then the coefficients are optionally quantized and encoded into bits. Different from the previous schemes, iWave++ is versatile: a single model supports both lossless and lossy compression, and also achieves arbitrary compression ratio by simply adjusting the quantization scale. iWave++ also features a carefully designed entropy coding engine to encode the coefficients progressively, and a de-quantization module for lossy compression. Experimental results show that lossy iWave++ achieves state-of-the-art compression efficiency compared with deep network-based methods;on the Kodak dataset, lossy iWave++ leads to 17.34 percent bits saving over BPG;lossless iWave++ achieves comparable or better performance than FLIF. Our code and models are available at https://***/mahaichuan/Versatile-Image-Compression.

关键词： Image coding Quantization (signal) Wavelet transforms Bit rate entropy coding Rate-distortion Deep network end-to-end optimization image compression lossless compression lossy compression wavelet transform

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A Block Adaptive Near-Lossless Compression Algorithm for Medical Image Sequences and Diagnostic Quality Assessment

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JOURNAL OF DIGITAL IMAGING 2020年第2期33卷 516-530页

作者： Sharma, Urvashi Sood, Meenakshi Puthooran, Emjee Jaypee Univ Informat Technol Dept Elect & Commun Waknaghat HP India

The near-lossless compression technique has better compression ratio than lossless compression technique while maintaining a maximum error limit for each pixel. It takes the advantage of both the lossy and lossless compression methods providing high compression ratio, which can be used for medical images while preserving diagnostic information. The proposed algorithm uses a resolution and modality independent threshold-based predictor, optimal quantization (q) level, and adaptive block size encoding. The proposed method employs resolution independent gradient edge detector (RIGED) for removing inter-pixel redundancy and block adaptive arithmetic encoding (BAAE) is used after quantization to remove coding redundancy. Quantizer with an optimum q level is used to implement the proposed method for high compression efficiency and for the better quality of the recovered images. The proposed method is implemented on volumetric 8-bit and 16-bit standard medical images and also validated on real time 16-bit-depth images collected from government hospitals. The results show the proposed algorithm yields a high coding performance with BPP of 1.37 and produces high peak signal-to-noise ratio (PSNR) of 51.35 dB for 8-bit-depth image dataset as compared with other near-lossless compression. The average BPP values of 3.411 and 2.609 are obtained by the proposed technique for 16-bit standard medical image dataset and real-time medical dataset respectively with maintained image quality. The improved near-lossless predictive coding technique achieves high compression ratio without losing diagnostic information from the image.

关键词： Near-lossless compression Quantizer Gradient edge detector Arithmetic encoding entropy coding

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On joint information embedding and lossy compression

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IEEE TRANSACTIONS ON INFORMATION THEORY 2005年第8期51卷 2998-3008页

作者： Maor, A Merhav, N Technion Israel Inst Technol Dept Elect Engn IL-32000 Haifa Israel

We consider the problem of optimum joint information embedding and lossy compression with respect to a fidelity criterion. The goal is to find the minimum achievable compression (composite) rate R-c as a function of the embedding rate R-c and the average distortion level Delta allowed, such that the average probability of error in decoding of the embedded message can be made arbitrarily small for sufficiently large block length. We characterize the minimum achievable composite rate for both the public and the private versions of the problem and demonstrate how this minimum can be approached in principle. We also provide an alternative single-letter expression of the maximum achievable embedding rate (embedding capacity) as a function of R-c and Delta, above which there exist no reliable embedding schemes.

关键词： entropy coding information embedding information hiding lossless/lossy compression rate-distortion theory watermarking

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Transform coding Techniques in HEVC

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IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING 2013年第6期7卷 978-989页

作者： Tung Nguyen Helle, Philipp Winken, Martin Bross, Benjamin Marpe, Detlev Schwarz, Heiko Wiegand, Thomas Heinrich Hertz Inst Nachrichtentech Berlin GmbH Fraunhofer Inst Telecommun Image & Video Coding Grp D-10587 Berlin Germany Heinrich Hertz Inst Nachrichtentech Berlin GmbH Fraunhofer Inst Telecommun Dept Image Proc D-10587 Berlin Germany Tech Univ Berlin D-10587 Berlin Germany

High Efficiency Video coding (HEVC) is the most recent jointly developed video coding standard of ITU-T Visual coding Experts Group (VCEG) and ISO/IEC Moving Picture Experts Group (MPEG). Although its basic architecture is built along the conventional hybrid block-based approach of combining prediction with transform coding, HEVC includes a number of coding tools with greatly enhanced coding-efficiency capabilities relative to those of prior video coding standards. Among these tools are new transform coding techniques that include the support for dyadically increasing transform block sizes ranging from 4 x 4 to 32 x 32, the partitioning of residual blocks into variable block-size transforms by using a quadtree-based partitioning dubbed as residual quadtree (RQT) as well as some properly designed entropy coding techniques for quantized transform coefficients of variable transform block sizes. In this paper, we describe these HEVC techniques for transform coding with a particular focus on the RQT structure and the entropy coding stage and demonstrate their benefit in terms of improved coding efficiency by experimental results.

关键词： entropy coding H.265 HEVC MPEG-H residual quadtree transform coding video compression

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