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Learned Image Compression With Efficient Cross-Platform entropy coding

IEEE JOURNAL ON EMERGING AND SELECTED TOPICS IN CIRCUITS AND SYSTEMS 2025年第1期15卷 72-82页

作者： Yang, Runyu Liu, Dong Wu, Feng Gao, Wen Univ Sci & Technol China Key Lab Brain Inspired Intelligent Percept & Cogni MOE Hefei 230027 Peoples R China Peking Univ Sch Comp Sci Beijing 100871 Peoples R China Peng Cheng Lab Shenzhen 518055 Peoples R China

Learned image compression has shown remarkable compression efficiency gain over the traditional image compression solutions, which is partially attributed to the learned entropy models and the adopted entropy coding engine. However, the inference of the entropy models and the sequential nature of the entropy coding both incur high time complexity. Meanwhile, the neural network-based entropy models usually involve floating-point computations, which incur inconsistent probability estimation and decoding failure in different platforms. We address these limitations by introducing an efficient and cross-platform entropy coding method, chain coding-based latent compression (CC-LC), into learned image compression. First, we leverage the classic chain coding and carefully design a block-based entropy coding procedure, significantly reducing the number of coding symbols and thus the coding time. Second, since CC-LC is not based on neural networks, we propose a rate estimation network as a surrogate of CC-LC during the end-to-end training. Third, we alternately train the analysis/synthesis networks and the rate estimation network for the rate-distortion optimization, making the learned latent fit CC-LC. Experimental results show that our method achieves much lower time complexity than the other learned image compression methods, ensures cross-platform consistency, and has comparable compression efficiency with BPG. Our code and models are publicly available at https://***/Yang-Runyu/CC-LC.

关键词： Image coding Estimation entropy coding entropy Computational modeling Training Symbols Transforms Circuits and systems Time complexity Block-based coding chain coding cross-platform consistency entropy coding learned image compression

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Reducing the Complexity of CCSDS 123.0-B-2 Hybrid entropy coding

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IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 2025年 22卷

作者： Zhang, Lei Song, Chengpeng Zhang, Longsheng Zhang, Peng Shenyang Aerosp Univ Coll Elect & Informat Engn Shenyang 110136 Liaoning Peoples R China

This letter addresses the complexity of the hybrid entropy encoder in the Consultative Committee for Space Data Systems (CCSDS) 123.0-B-2 compression standard and proposes an improved encoding method. By eliminating the refresh table from the original standard, simplifying the encoding process, and using forward decoding, the proposed method significantly reduces encoding complexity and enhances error resilience. The improved algorithm is particularly optimized for handling high-resolution accumulators, reducing bitstream redundancy while maintaining compression performance comparable to the original standard. Experimental results demonstrate that the new algorithm excels in both lossless and lossy compression, achieving higher compression ratios (CRs) and better image quality, making it well-suited for satellite platform applications with bandwidth and power consumption constraints.

关键词： Image coding Standards Decoding Codes Symbols Indexes Complexity theory Tail Switches entropy coding Compression standard hybrid coding hyperspectral imaging (HSI) image compression near-lossless

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entropy coding Aided Adaptive Subcarrier-Index Modulated OFDM

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IEEE ACCESS 2018年 6卷 7739-7752页

作者： Kadir, Mohammad Ismat Zhang, Hongming Chen, Sheng Hanzo, Lajos Khulna Univ Elect & Commun Engn Discipline Khulna 9208 Bangladesh Univ Southampton Sch Elect & Comp Sci Southampton SO17 1BJ Hants England

We propose entropy coding-aided adaptive subcarrier-index-modulated orthogonal frequency division multiplexing (SIM-OFDM). In conventional SIM-OFDM, the indices of the subcarriers activated are capable of conveying extra information. We propose the novel concept of compressing the index information bits by employing the Huffman coding. The probabilities of the different subcarrier activation patterns are obtained from an optimization procedure, which improves the performance of the scheme. Both the maximum-likelihood as well as the logarithmic-likelihood ratio-based soft detector may be employed for detecting the subcarriers activated as well as the information mapped to the classic constellation symbols. As an additional advantage of employing the variable-length Huffman codebook, all the legitimate subcarrier activation patterns may be employed, whereas the conventional SIM-OFDM is capable of using only a subset of the patterns. Our simulation results show that an improved performance is attainable by the proposed system.

关键词： Orthogonal frequency division multiplexing (OFDM) subcarrier index modulation-orthogonal frequency division multiplexing (SIM-OFDM) entropy coding capacity energy-efficiency (EE)

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entropy coding of compressed feature parameters for distributed speech recognition

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SPEECH COMMUNICATION 2010年第5期52卷 405-412页

作者： Lee, Young Han Kim, Hong Kook Gwangju Inst Sci & Technol Dept Informat & Commun Kwangju 500712 South Korea

In this paper, we propose several entropy coding methods to further compress quantized mel-frequency cepstral coefficients (MFCCs) used for distributed speech recognition (DSR). As a standard DSR front-end, the European Telecommunications Standards Institute (ETSI) published an extended front-end that includes the split-vector quantization of MFCCs and voicing class information. By exploring entropy variances of compressed MFCCs according to the voicing class of the analysis frame and the amount of the entropy due to MFCC subvector indices, voicing class-dependent and subvector-wise Huffman coding methods are proposed. In addition, differential Huffman coding is then applied to further enhance the coding gain against class-dependent and subvector-wise Huffman codings. Subsequent experiments show that the average bit-rate of the subvector-wise differential Huffman coding is measured at 33.93 bits/frame, which is the smallest among the proposed Huffman coding methods, whereas that of a traditional Huffman coding that does not consider voicing class and encodes with a single Huffman coding tree for all the subvectors is measured at 42.22 bits/frame for the TIMIT database. In addition, we evaluate the performance of the proposed Huffman coding methods applied to speech in noise by using the Aurora 4 database, a standard speech database for DSR. As a result, it is shown that the subvector-wise differential Huffman coding method provides the smallest average bit-rate. (C) 2010 Elsevier B.V. All rights reserved.

关键词： entropy coding Distributed speech recognition Huffman coding Mel-frequency cepstral coefficient Voicing class

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entropy coding FOR LOW-BIT-RATE VISUAL TELECOMMUNICATIONS

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 1987年第7期5卷 1175-1183页

作者： ELNAHAS, SE DUNHAM, JG SO METHODIST UNIV DEPT ELECT ENGN DALLAS TX 75275 USA

Several compression techniques need to be integrated for the achievement of effective low-bit-rate coding of moving images. Image entropy codes are used in conjunction with either predictive or transform coding methods. In this paper, we investigate the possible advantages of using arithmetric codes for image entropy coding. A theory of source modeling is established based on the concept of source parsing and conditioning trees. The key information-theoretic properties of conditioning trees are discussed along with algorithms for the construction of optimal and suboptimal trees. The theory and algorithms are then applied to evaluating the performance of entropy coding for the discrete cosine transform coefficients of digital images from the "Walter Cronkite" video sequence. The performance of arithmetic codes is compared to that of a traditional combination of run length and Huffman codes. The results indicate that binary arithmetic codes outperform run length codes by a factor of 55 percent for low-rate coding of the zero-valued coefficients. Hexadecimal arithmetic codes provide a coding rate improvement as high as 28 percent over truncated Huffman codes for the nonzero coefficients. The complexity of these arithmetic codes is suitable for practical implementation.

关键词： entropy coding Image coding Arithmetic Discrete cosine transforms Pulse modulation Pixel Image reconstruction Karhunen-Loeve transforms Layout Transform coding

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entropy coding FOR A HYBRID SCHEME WITH MOTION COMPENSATION IN SUBPRIMARY RATE VIDEO TRANSMISSION

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 1987年第7期5卷 1166-1174页

作者： KOGA, T OHTA, M C & C Information Technology Research Laboratories NEC Corporation Limited Kawasaki Japan

entropy coding has been investigated for motion-compensated interframe (MC) prediction followed by two-dimensional discrete cosine transform (DCT) for prediction error. In particular, variable word length coding methods for motion vector and transform coefficients have been discussed assuming low bit rate such as 384 kbits/s for transmission of videoconference sequences. For motion vector information, it is advantageous to employ a one-dimensional code set common to both horizontal and vertical components of motion vectors. The code set can be obtained using a combined distribution of the two components. In order to encode transform coefficients, different methods are applied to significant and insignificant blocks. Run-length coding is adequate for representing clusters of insignificant blocks. In encoding transform coefficients in significant blocks, a zone coding method which encodes transform coefficients within a minimum area enclosing all nonzero coefficients is suitable. Simulation of video sequences shows that a combination of the coding methods described here can achieve high coding efficiency for videoconference sequences.

关键词： entropy coding Motion compensation Discrete cosine transforms Videoconference Transform coding Bit rate Encoding Motion detection Motion analysis Discrete transforms

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entropy coding and entropy coding Improvements of JPEG XS

Entropy Coding and Entropy Coding Improvements of JPEG XS

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Data Compression Conference (DCC)

作者： Richter, Thomas Keinert, Joachim Descampe, Antonin Rouvroy, Gael Fraunhofer Inst Integrierte Schaltungen IIS Wolfsmantel 33 D-91058 Erlangen Germany IntoPIX Sa Rue Emile Francqui 9 B-1435 Mont St Guibert Belgium

ISBN: (纸本)9781538648834

JPEG XS is a new standard for low-latency and low-complexity coding designed by the JPEG committee. Unlike former developments, optimal rate distortion performance is only a secondary goal;the focus of JPEG XS is to enable cost-efficient, easy to parallelize implementations suitable for FPGAs or GPUs. In this article, we shed some light on the entropy coding back-end of JPEG XS and introduce modifications of the entropy coding stage currently under discussion that improve objective and subjective quality of the compressed images without compromising the parallelism of the original algorithm.

关键词： Transform coding Quantization (signal) entropy coding Standards Rate-distortion Image coding

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A Low-Complexity Bit-Plane entropy coding and Rate Control for 3-D DWT Based Video coding

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IEEE TRANSACTIONS ON MULTIMEDIA 2013年第8期15卷 1786-1799页

作者： Belyaev, Evgeny Egiazarian, Karen Gabbouj, Moncef Tampere Univ Dept Signal Proc FIN-33101 Tampere Finland

This paper is dedicated to fast video coding based on three-dimensional discrete wavelet transform. First, we propose a novel low-complexity bit-plane entropy coding of wavelet subbands based on Levenstein zero-run coder for low entropy contexts and adaptive binary range coder for other contexts. Second, we propose a rate-distortion efficient criterion for skipping 2-D wavelet transforms and entropy encoding based on parent-child subband tree. Finally, we propose one pass rate control which uses virtual buffer concept for adaptive Lagrange multiplier selection. Simulations results show that the proposed video codec has a much lower computational complexity (from 2 to 6 times) for the same quality level compared to the H. 264/AVC standard in the low complexity mode.

关键词： entropy coding rate control 3-D DWT.

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entropy coding Improvement for Low-complexity Compressive Auto-encoders

Entropy Coding Improvement for Low-complexity Compressive Au...

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Data Compression Conference (DCC)

作者： Galpin, Franck Balcilar, Muhammet Lefebvre, Frederic Racape, Fabien Hellier, Pierre InterDigital Inc Rennes France

ISBN: (纸本)9798350347951

End-to-end image and video compression using auto-encoders (AE) offers new appealing perspectives in terms of rate-distortion gains and applications. While most complex models are on par with the latest compression standard like VVC/H.266 on objective metrics, practical implementation and complexity remain strong issues for real-world applications. We propose a practical implementation suitable for realistic applications. We demonstrate that some gains can be achieved on top low-complexity AE, even when using simpler implementation. The proposed implementation also allows a direct integration of such approaches on a variety of platforms and code is made available as a pure C++ standalone codec[1]: replace the greedy gdn/igdn activations by Relu/Relu activations distillate the neural codec's with a full 16-bits integer network, learn a new context switching based conditional entropy model, rate distortion optimization process using only the distillated decoder. All AE used the CompressAl[1] framework and training conditions, with 200 epochs and a 36.8kMAC/pix decoder. Proposed methods are implemented using the lightweight framework SADL [2] as a pair of standalone encoder/decoder in pure C++. [GRAPHICS] .

关键词： autoencoder entropy coding image compression

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BLOCK TRUNCATION coding WITH entropy coding

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IEEE TRANSACTIONS ON COMMUNICATIONS 1995年第2-4期43卷 1677-1685页

作者： FRANTI, P NEVALAINEN, O Department of Computer Science University of Turku Turku Finland

Block Truncation coding (ETC) is a simple and fast image compression algorithm which achieves constant bit rate of 2.0 bits per pixel, The method is however suboptimal. In the present paper we propose a modification of ETC in which the compression ratio will be improved by coding the quantization data and the bit plane by arithmetic coding with an adaptive modelling scheme. The results compare favorable with other ETC variants. The bit rate for test image Lena is 1.53 bits per pixel with the mean square error of 16.51.

关键词： compression ratio constant bit rate (CBR) pixel image compression algorithm entropy coding arithmetic coding Mean square error Block truncation coding

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