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An enhanced entropy coding scheme for HEVC

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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Fast Mode Selection for HEVC Intra-Frame coding With entropy coding Refinement Based on a Transparent Composite Model

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2015年第9期25卷 1521-1532页

作者： Hu, Nan Yang, En-Hui Univ Waterloo Dept Elect & Comp Engn Waterloo ON N2L 3G1 Canada

In comparison with H.264/Advanced Video coding, the newest video coding standard, High Efficiency Video coding (HEVC), improves video coding rate-distortion (RD) performance, but at the price of significant increase in its encoding complexity, especially, in intra-mode decision due to the adoption of more complex block partitions and more candidate intra-prediction modes (IPMs). To reduce the mode decision complexity in HEVC intra-frame coding, while maintaining its RD performance, in this paper, we first formulate the mode decision problem in intra-frame coding as a Bayesian decision problem based on the newly proposed transparent composite model (TCM) for discrete cosine transform coefficients, and then present an outlier-based fast intra-mode decision (OIMD) algorithm. The proposed OIMD algorithm reduces the complexity using outliers identified by TCM to make a fast coding unit split/nonsplit decision and reduce the number of IPMs to be compared. To further take advantage of the outlier information furnished by TCM, we also refine entropy coding in HEVC by encoding the outlier information first, and then the actual mode decision conditionally given the outlier information. The proposed OIMD algorithm can work with and without the proposed entropy coding refinement. Experiments show that for the all-intra-main test configuration of HEVC: 1) when applied alone, the proposed OIMD algorithm reduces, on average, the encoding time (ET) by 50% with 0.7% Bjontegaard distortion (BD)-rate increase and 2) when applied in conjunction with the proposed entropy coding refinement, it reduces, on average, both the ET by 50% and BD-rate by 0.15%.

关键词： Complexity reduction entropy coding High Efficiency Video coding (HEVC) intra coding mode decision transparent composite model (TCM)

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Determination of huffman parameters for memory-constrained entropy coding of multiple sources

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IEEE SIGNAL PROCESSING LETTERS 1997年第3期4卷 65-67页

作者： Lee, SJ Lee, CW Institute of New Media and Communications the School of Electrical Engineering Seoul National University Seoul South Korea

In Huffman coding of multiple sources with a constrained memory, determination of Huffman parameters has a great effect on coding performance. This letter presents an efficient method for determining the Huffman param... 详细信息

关键词： entropy coding Signal processing algorithms Iterative algorithms Decoding Huffman coding Memory management Encoding Vector quantization Bit rate Search methods

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High-Order entropy coding for Images

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 1992年第1期2卷 87-89页

作者： Tzou, Kou-Hu BELLCORE Red Bank NJ 07701 USA

A preliminary study shows the effectiveness of high-order entropy coding for 2-D data. The incremental conditioning tree extension method is the key element for reducing the complexity of high-order statistical coding. The determination of the conditioning state in the nonfull tree for an underlying sample is, in functionality, similar to the extraction of a codeword from a variable length coded bit string. Therefore, the hardware structure used for decoding variable length codes can be applied to determine the conditioning state based on data in the causal region.< >

关键词： entropy coding Higher order statistics Probability Source coding Bit rate Signal processing Conferences Arithmetic Binary trees Equations

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On Improving JPEG entropy coding by means of Sub-Stream Extraction

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IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS 2012年第11期E95D卷 2737-2740页

作者： Kim, Youngjin Shin, Hyun Joon Choi, Jung-Ju Wee, Youngcheul Ajou Univ Dept Informat & Comp Engn Suwon 443749 South Korea Ajou Univ Dept Digital Media Suwon 443749 South Korea

We introduce an entropy coding method to enhance the compression efficiency of JPEG. Because run-length coding and early-termination work more effectively for longer zero sequences, we extract ones and negative ones from the coefficients and reduce the magnitude of all coefficients by one. The extracted coefficients are encoded with a designated entropy coding method. The proposed method can transmit images in two parts progressively, where the first contains JPEG-compatible image with a small amount of degradation and the second is used to add fine details. Our method improves the compression ratio by more than 5% without sacrificing the efficiency of JPEG.

关键词： JPEG entropy coding sub-strewn extraction

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SUBJECTIVE EVALUATION OF AN ADAPTIVE DIFFERENTIAL VOICE ENCODER WITH OVER-SAMPLING AND entropy coding

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IEEE TRANSACTIONS ON COMMUNICATIONS 1978年第2期26卷 201-208页

作者： HANSON, BA DONALDSON, RW UNIV BRITISH COLUMBIA DEPT ELECT ENGNVANCOUVER V6T 1W5BCCANADA

An adaptive differential speech encoder was assessed using subjective evaluation procedures. The coder's adaptive quantizer was similar to the one used by Cohn and Melsa [1] and the predictor involved nonadaptive previous-sample feedback. The digital channel used to transmit the quantizer output levels was assumed error-free. Paired comparison tests were used to obtain scaled isopreference contours on the N-f plane, where N and f denote, respectively, the number of quantizer output levels and the sampling rate relative to the Nyquist rate. These contours were used to determine the subjective signal-to-noise ratio vs. f and N , maximum subjective signal-signal-to-noise ratios vs. bit rate, optimum values of f and N , and bit-rate savings which occur when entropy coding is used instead of natural coding of the quantizer output levels. entropy coding yielded a bit rate approximately equal to threequarters that for natural coding and Nyquist-rate sampling minimized the bit rate in each case. Savings of from one to two bits occurred when ADPCM was compared with nonadaptive DPCM. The fact that our system was better than others for f \simeq 1.0 but worse for f \gsim 2.0 indicates the need to modify our quantizer adaptation algorithm as the sampling rate increases relative to the Nyqusit rate.

关键词： entropy coding Bit rate Sampling methods Signal to noise ratio Decoding Speech analysis Speech coding Feedback Testing Digital communication

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Vector quantization for entropy coding of image subbands

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IEEE TRANSACTIONS ON IMAGE PROCESSING 1992年第4期1卷 526-533页

作者： Senoo, Takanori Girod, Bemd MIT Media Lab Vis & Modeling Grp Cambridge MA 02139 USA

Vector quantization for entropy coding of image subbands is investigated. Rate distortion curves are computed with mean square error as a distortion criterion. We show that full search entropy constrained vector quantization of image subbands results in the best performance, but is computationally expensive. Lattice quantizers yield a coding efficiency almost indistinguishable from optimum full-search entropy-constrained vector quantization (EC-VQ). Orthogonal lattice quantizers were found to perform almost as well as lattice quantizers derived from dense sphere packings. An optimum bit allocation rule based on a Lagrange multiplier formulation is applied to subband coding. coding results are shown for a still image.

关键词： Vector quantization entropy coding Image coding Lattices Books Rate-distortion Bit rate Image storage Encoding Iterative algorithms

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ADAPTIVE NOISE SPECTRAL SHAPING AND entropy coding IN PREDICTIVE coding OF SPEECH

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IEEE TRANSACTIONS ON ACOUSTICS SPEECH AND SIGNAL PROCESSING 1979年第1期27卷 63-73页

作者： MAKHOUL, J BEROUTI, M Bolt Beranek and Newman 슠Inc. Cambridge MA USA

We report on research to code speech at 16 kbit/s with the goal of having the quality of the coded speech be equal to that of the original. Some of the original speech had been corrupted by noise and distortions typical of long-distance telephone lines. The basic structure chosen for our system was adaptive predictive coding. However, the rigorous requirements of this work led to a new outlook on the different aspects of adaptive predictive coding. We have found that the pitch predictor is not cost-effective on balance and may be eliminated. Solutions are presented to deal with the two types of quantization noise: clipping and granular noise. The clipping problem is completely eliminated by allowing the number of quantizer levels to increase indefinitely. An appropriate self-synchronizing variable-length code is proposed to minimize the average data rate; the coding scheme seems to be adequate for all speech and all conditions tested. The granular noise problem is treated by modifying the predictive coding system in a novel manner to include an adaptive noise spectral shaping filter. A design for such a filter is proposed that effectively eliminates the perception of granular noise.

关键词： Noise shaping entropy coding Predictive coding Speech enhancement Speech coding Filters Telephony Adaptive systems Quantization Automatic testing

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Compressed Data Organization for High Throughput Parallel entropy coding 38

Compressed Data Organization for High Throughput Parallel En...

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Conference on Applications of Digital Image Processing XXXVIII

作者： Said, Amir Mahfoodh, Abo-Talib Yea, Sehoon Qualcomm Technol Inc San Diego CA 92121 USA Michigan State Univ E Lansing MI 48824 USA LG Elect Seoul South Korea

ISBN: (纸本)9781628417654

The difficulty of parallelizing entropy coding is increasingly limiting the data throughputs achievable in media compression in this work we analyze what are the fundamental limitations, using finite-state-machine models for identifying the best manlier of separating tasks that can be processed independently, while minimizing compression losses. This analysis confirms previous works showing that effective parallelization is feasible only if the compressed data is organized in a proper way, which is quite different from conventional formats. The proposed new formats exploit the fact that optimal compression is not affected by the arrangement of coded bits, but it goes further in exploiting the decreasing cost of data processing and memory. Additional advantages include the ability to use, within this framework, increasingly more complex data modeling techniques, and the freedom to mix different types of coding. We confirm the parallelization effectiveness using coding simulations that run On multi-core processors, and show how throughput scales with the number of cores, and analyze the additional bit-rate overhead.

关键词： entropy coding parallel computation signal compression

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GPU-Intensive Fast entropy coding Framework for Neural Image Compression

GPU-Intensive Fast Entropy Coding Framework for Neural Image...

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IEEE International Conference on Visual Communications and Image Processing (VCIP) - Visual Communications in the Era of AI and Limited Resources

作者： Akutsu, Hiroaki Naruko, Takahiro Suzuki, Akifumi Hitachi Ltd Res & Dev Grp Tokyo Japan

ISBN: (纸本)9781728185514

Neural compression has benefited from technological advances such as convolutional neural networks (CNNs) to achieve advanced bitrates, especially in image compression. In neural image compression, an encoder and a decoder can run in parallel on a GPU, so the speed is relatively fast. However, the conventional entropy coding for neural image compression requires serialized iterations in which the probability distribution is estimated by multi-layer CNNs and entropy coding is processed on a CPU. Therefore, the total compression and decompression speed is slow. We propose a fast, practical, GPU-intensive entropy coding framework that consistently executes entropy coding on a GPU through highly parallelized tensor operations, as well as an encoder, decoder, and entropy estimator with an improved network architecture. We experimentally evaluated the speed and rate-distortion performance of the proposed framework and found that we could significantly increase the speed while maintaining the bitrate advantage of neural image compression.

关键词： neural image compression entropy coding GPU

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