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Autonomous Parameter Adjustment Method for Lossless Data Compression on Adaptive Stream-Based entropy coding

IEEE ACCESS 2020年 8卷 186890-186903页

作者： Yamagiwa, Shinichi Kuwabara, Suzukaze Univ Tsukuba Fac Engn Informat & Syst Tsukuba Ibaraki 3058573 Japan Univ Tsukuba Dept Comp Sci Tsukuba Ibaraki 3058573 Japan

As speed of communication data path is drastically improved in this decade due to the high data rate, evolutional technology is demanded to address the fast communication implementation. In this paper, we focus on data compression technology to speed up the communication data path. We have proposed a stream-based data compression called ASE coding. It compresses data stream based on the instantaneous data entropy without buffering and stalling for the compression processes. It is also suitable for hardware implementation. However, the stream-based data compression works heuristically with sensitive parameters that affect to the data compression ratio. If the parameters are statically configured, it does not follow the dynamic data entropy, and thus, the data compression performance becomes unstable. In this paper, we will disseminate the parameters, discuss the behaviors of those parameters and propose its autonomous adjustment methods. We will also propose adjustment algorithms for those parameters that follow the data entropy of the input data stream autonomously. Through experimental evaluations applying the algorithms, we will confirm the parameters are adjusted with depending on the data entropy in the data stream. And then, the compression ratio becomes stable as the compressor exploits the minimal entropy adaptively.

关键词： entropy Table lookup Heuristic algorithms Channel coding Huffman coding Lossless data compression parameter adjustment entropy coding

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An efficient parallel entropy coding method for JPEG compression based on GPU

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JOURNAL OF SUPERCOMPUTING 2022年第2期78卷 2681-2708页

作者： Zhu, Fushun Yan, Hua Sichuan Univ Coll Elect & Informat Engn Chengdu 610065 Sichuan Peoples R China

The fast JPEG image compression algorithm is a requisite in many applications such as high-speed video measurement systems and digital cinema. Many existing methods have implemented the JPEG compression in parallel based on GPU except for entropy coding, which is a variable-length coding method and seems like a better fit for sequential implementation. However, entropy coding is an essential part of the JPEG compression system and typically takes up a large proportion of the time when implemented on the CPU. To tackle this problem, we propose an efficient parallel entropy coding (EPEnt) method for parallel JPEG compressing. The proposed method conducts entropy coding in three parallel steps: coding, shifting, and stuffing. Specifically, according to the different characteristics of image components, we devise thread-based and warp-based functions in the coding stage to further improve the efficiency under guaranteeing image quality, respectively. We apply the proposed method to the parallel JPEG compression system and evaluate the performance based on compute unified device architecture (CUDA). The experimental results demonstrate that compared with sequential implementation, the maximum speedup ratio of entropy coding can reach 39 times without affecting compressed images quality. Meanwhile, the whole JPEG compression process efficiency increases by at least 28% compared with state-of-the-art parallel methods in terms of speedup ratio.

关键词： Real-time systems JPEG entropy coding Parallel algorithm CUDA

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Scalable Audio coding Using Trellis-Based Optimized Joint entropy coding and Quantization

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IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING 2016年第12期24卷 2288-2300页

作者： Movassagh, Mahmood Kabal, Peter McGill Univ Dept Elect & Comp Engn Montreal PQ H3A 0E9 Canada

There is a considerable performance gap between the current scalable audio coding schemes and a nonscalable coder operating at the same bitrate. This suboptimality results from the independent coding of the layers in these systems. One of the aspects that plays a role in this suboptimality is the entropy coding. In practical audio coding systems including MPEG advanced audio coding (AAC), the transform domain coefficients are quantized using an entropy-constrained quantizer. InMPEG-4 scalable AAC (S-AAC), the quantization and coding are performed separately at each layer. In case of Huffman coding, the redundancy introduced by the entropy coding at each layer is larger at lower quantization resolutions. Also, the redundancy for the overall coder becomes larger as the number of layers increases. In fact, there is a trade-off between the overall redundancy and the fine-grain scalability in which the bitrate per layer is smaller and more layers are required. In this paper, a fine-grain scalable coder for audio signals is proposed where the entropy coding of a quantizer is made scalable via joint design of entropy coding and quantization. By constructing a Huffman-like coding tree where the internal nodes can be mapped to the reconstruction points, the tree can be pruned at any internal node to control the rate-distortion (RD) performance of the encoder in a fine-grain manner. A set of metrics and a trellis-based approach is proposed to create a coding tree so that an appropriate path is generated on the RD plane. The results show the proposed method outperforms the scalable audio coding performed based on reconstruction error quantization as used in practical systems, e.g., in S-AAC.

关键词： Audio coding bit-rate scalability entropy coding quantization AAC SLS

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ECG compression using uniform scalar dead-zone quantization and conditional entropy coding

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MEDICAL ENGINEERING & PHYSICS 2008年第4期30卷 523-530页

作者： Chen, Jianhua Wang, Fuyan Zhang, Yufeng Shi, Xinling Yunnan Univ Dept Elect Engn Kunming 650091 Peoples R China

A new wavelet-based method for the compression of electrocardiogram (ECG) data is presented. A discrete wavelet transform (DWT) is applied to the digitized ECG signal. The DWT coefficients are first quantized with a uniform scalar dead-zone quantizer, and then the quantized coefficients are decomposed into four symbol streams, representing a binary significance stream, the signs, the positions of the most significant bits, and the residual bits. An adaptive arithmetic coder with several different context models is employed for the entropy coding of these symbol streams. Simulation results on several records from the MIT-BIH arrhythmia database show that the proposed coding algorithm outperforms some recently developed ECG compression algorithms. (C) 2007 IPEM. Published by Elsevier Ltd. All rights reserved.

关键词： ECG compression wavelet transform quantization entropy coding

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Joint image compression-encryption scheme using entropy coding and compressive sensing

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NONLINEAR DYNAMICS 2019年第3期95卷 2235-2261页

作者： Song, Yanjie Zhu, Zhiliang Zhang, Wei Guo, Li Yang, Xue Yu, Hai Northeastern Univ Software Coll Shenyang 110819 Liaoning Peoples R China Northeastern Univ Sch Comp Sci & Engn Shenyang 110819 Liaoning Peoples R China

Recently, compressive sensing (CS)-based joint compression-encryption schemes have been widely investigated due to their high efficiency and good security for images. However, the existing schemes typically have a lower compression ratio (CR), and there may be a flaw during their compression processes. Therefore, in this paper, according to the intrinsic features of images, we propose a novel compression architecture to enhance the CR. Meanwhile, based on this architecture, a joint image compression-encryption scheme using entropy coding and CS is designed to implement a complete compression and encryption process. In this joint scheme, a presented bit-level lossless compression-encryption algorithm based on entropy coding for the higher bit-planes is incorporated to improve the quality of the reconstructed image and ensure the security. Alternately, this joint scheme also contains an improved CS-based lossy compression-encryption algorithm for the lower bit-planes, which can guarantee the efficiency and security. Through the cooperation between the proposed lossless and lossy coding, the higher reconstruction performance can be achieved. SHA-256 is combined with all initial keys in the proposed joint scheme to generate the updated keys for chaos cryptosystem to maintain high security and resist some common attacks. Experimental and analytical results illustrate the superiority of the proposed joint scheme compared with the existing compression-encryption schemes and JPEG, as well as good encryption performance.

关键词： Joint image compression-encryption Compressive sensing entropy coding Chaos Bit-plane

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HDVC: Deep Video Compression With Hyperprior-Based entropy coding

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IEEE ACCESS 2024年 12卷 17541-17551页

作者： Hu, Yusong Jung, Cheolkon Qin, Qipu Han, Jiang Liu, Yang Li, Ming Xidian Univ Sch Elect Engn Xian 710071 Peoples R China Guangdong OPPO Mobile Telecommun Corp Ltd Dongguan 523860 Peoples R China

In this paper, we propose deep video compression with hyperprior-based entropy coding, named HDVC. The proposed method is based on the deep video compression (DVC) framework that replaces traditional block-based video compression with end-to-end video compression based on deep learning, aiming to improve compression efficiency and reduce computational complexity while maintaining visual quality. Based on the DVC framework, we introduce hyperprior-based entropy coding into motion compression and optimize motion vector estimation (i.e. optical flow estimation) using window attention and fast residual channel attention. Moreover, we introduce residual channel attention intermediate module into both encoding and decoding to enhance residuals and the quality of reconstructed frames. We adopt hyperprior-based entropy coding in residual compression to model feature distribution. Besides, we use learned image compression for intraframe coding based on fast residual channel attention network to generate reference frames. Experimental results show that the proposed method achieves better PSNR and MS-SSIM performance than both traditional block-based and recent deep learning-based video compression methods on UVG dataset.

关键词： Image coding Video compression Optical imaging Adaptive optics Estimation entropy coding Image reconstruction Deep learning Hyperprior entropy coding learned video compression deep learning end-to-end

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INTERFRAME DPCM WITH ADAPTIVE QUANTIZATION AND entropy coding

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IEEE TRANSACTIONS ON COMMUNICATIONS 1982年第8期30卷 1888-1899页

作者： ZETTERBERG, LH ERICSSON, S BRUSEWITZ, H Telecommunication Theory Royal Institute of Technology Stockholm Sweden

The object of this work has been to study encoding of monochrome pictures with a rate of about 1 bit per picture element (pel). Differential pulse code modulation, DPCM, has been chosen to make the system reasonably simple. This motivates the choice of a fixed three-dimensional predictor made separable in time and space. It essentially amounts to encoding the frame difference using a two dimensional predictor. To improve performance, the quantizer is made adaptive and the encoding is combined with delayed decision. A three-level quantizer is being used with an adaptive scheme that works with either forward or backward estimation. The output from the DPCM unit is redundant and we have adopted entropy coding to further reduce the bit rate. The entropy measure is also used to adjust the quantizer parameters to achieve the desired bit rate of 1 bit/pel. Encoding experiments were carried out on a complex videophone scene by means of computer simulations.

关键词： Quantization entropy coding Encoding Bit rate Pulse modulation Delay Dynamic range Modulation coding Forward contracts Layout

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Efficient entropy coding scheme for H 264/AVC lossless video coding

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SIGNAL PROCESSING-IMAGE COMMUNICATION 2010年第9期25卷 687-696页

作者： Kim, Seung-Hwan Heo, Jin Ho, Yo-Sung Gwangju Inst Sci & Technol Dept Informat & Commun Kwangju 500712 South Korea Univ So Calif Ming Hsieh Dept Elect Engn Los Angeles CA 90089 USA Univ So Calif Inst Signal & Image Proc Los Angeles CA 90089 USA

Context-based adaptive variable length coding (CAVLC) and context-based adaptive binary arithmetic coding (CABAC) are entropy coding methods employed in the H 264/AVC standard Since these entropy coders are originally designed for encoding residual data which are zigzag scanned and quantized transform coefficients they cannot provide adequate coding performance for lossless video coding where residual data are not quantized transform coefficients but the differential pixel values between the original and predicted pixel values Therefore considering the statistical characteristics of residual data in lossless video coding we newly design each entropy coding method based on the conventional entropy coders in H 264/AVC From the experimental result we have verified that the proposed method provides not only positive bit-saving of 8% but also reduced computational complexity compared to the current H 264/AVC lossless coding mode (c) 2010 Elsevier B V All rights reserved

关键词： H 264/AVC CAVLC CABAC Lossless video coding entropy coding

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Context-based entropy coding in AVS video coding standard

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SIGNAL PROCESSING-IMAGE COMMUNICATION 2009年第4期24卷 263-276页

作者： Zhang, Li Wang, Qiang Zhang, Ning Zhao, Debin Wu, Xiaolin Gao, Wen Chinese Acad Sci Inst Comp Technol Key Lab Intelligent Informat Proc Beijing Peoples R China Harbin Inst Technol Dept Comp Sci & Engn Harbin 150006 Peoples R China McMaster Univ Dept Elect & Comp Engn Hamilton ON L8S 4L8 Canada Peking Univ Sch Elect Engn & Comp Sci Inst Digital Media Beijing 100871 Peoples R China

In this paper, two context-based entropy coding schemes for AVS Part-2 video coding standard are presented. One is Context-based 2D Variable Length coding (C2DVLC) as a low complexity entropy coding scheme for AVS Part-2 Jizhun profile. C2DVLC uses Multiple 2D-VLC tables to exploit the statistical features of DCT coefficients for higher coding efficiency. Exponential-Golomb codes are applied in C2DVLC to code the pairs of the run-length of zero coefficients and the non-zero coefficients for lower storage requirement. The other is Context-based Binary Arithmetic coding (CBAC) as an enhanced entropy coding scheme for AVS Part-2 Jiaqiang profile. CBAC utilizes all previously coded coefficient magnitudes in a DCT block for context modeling. This enables adaptive arithmetic coding to exploit the redundancy of the high-order Markov process in DCT domain with a few contexts. In addition, a context weighting technique is used to further improve CBAC's coding efficiency. Moreover, CBAC is designed to be compatible to C2DVLC in coding elements which simplifies the implementations. The experimental results demonstrate that both C2DVLC and CBAC can achieve comparable or even slightly higher coding performance when compared to Context-Adaptive Variable Length coding (CAVLC) in H.264/AVC baseline profile and Context-Based Adaptive Binary Arithmetic coding (CABAC) in H.264/AVC main profile respectively. (C) 2009 Elsevier B.V. All rights reserved.

关键词： AVS DCT video coding entropy coding Context modeling Variable length coding Arithmetic coding

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An enhanced entropy coding scheme for HEVC

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SIGNAL PROCESSING-IMAGE COMMUNICATION 2016年 44卷 108-123页

作者： Gao, Min Fan, Xiaopeng Zhao, Debin Gao, Wen Harbin Inst Technol Dept Comp Sci & Technol Harbin 150001 Peoples R China Peking Univ Sch Elect Engn & Comp Sci Beijing 100000 Peoples R China

This paper presents a modification to Context-based Adaptive Binary Arithmetic coding (CABAC) in High Efficiency Video coding (HEVC), which includes an improved context modeling for transform coefficient levels and a binary arithmetic coding (BAC) engine with low memory requirement. In the improved context modeling for transform coefficient levels, the context model index for significance map is dependent on the number of the significant neighbors covered by a local template and its position within transform block (TB). To limit the total number of context models for significance map, TBs are split into different regions based on the coefficient position. The same region in different TBs shares the same context model set. For the first and second bins of the truncated unary scheme of absolute level minus one, their context model indices depend on the neighbors covered by a local template of the current transform coefficient level. Specifically, the context model index for the first bin is determined by the number of neighbors covered by the local template with absolute magnitude equal to 1 and larger than 1;for the second bin, its context model index is determined by the number of neighbors covered by the local template with absolute magnitude larger than 1 and larger than 2. Moreover, TB is also split into different regions to incorporate the coefficient position in the context modeling of the first bin in luma component. In the BAC engine with low memory requirement, the probability is estimated based on a multi-parameter probability update mechanism, in which the probability is updated with two different adaption speeds and use the average as the estimated probability for the next symbol. Moreover, a multiplication with low bit capacities is used in the coding interval subdivision to substitute the large look-up table to reduce its memory consumption. According to the experiments conducted on HM14.0 under HEVC main profile, the improved context modeling for trans

关键词： HEVC CABAC entropy coding Context modeling Binary arithmetic coding

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