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检索条件"主题词=entropy coding"

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Cache Compression with Golomb-Rice Code and Quantization for Convolutional Neural Networks

Cache Compression with Golomb-Rice Code and Quantization for...

引用

IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Seung-Hwan Bae Hyuk-Jae Lee Hyun Kim Department of Electrical and Computer Engineering Inter-University Semiconductor Research Center Seoul National University Seoul Korea Department of Electrical and Information Engineering Seoul National University of Science and Technology Seoul Korea

Cache compression schemes reduce the cache miss rate by increasing the effective cache capacity and consequently, reduce memory access and power consumption. Therefore, cache compression is beneficial for applications with heavy memory traffic, including convolutional neural network (CNN). In this paper, a new cache compression of a floatingpoint number is proposed for CNNs. The exponent is compressed using the Golomb-Rice code, instead of the Huffman code, for an efficient hardware implementation. The compression syntax is carefully designed so that the size of compressed data is not very far from the entropy, which is the theoretical limit, by distinguishing two different types of data used in CNNs. On the other hand, since the mantissa of CNNs data can be hardly compressed by entropy coding, it is simply quantized for data reduction that may not degrade the CNN performance significantly thanks to the error robustness of CNNs. The quantization reduces 23 bits of a mantissa to 4 bits. The experimental results show that the miss rate of a 1 MB compressed cache with the proposed compression method applied is almost similar to that of an uncompressed 2 MB cache without any decrease of the CNN accuracy.

关键词： Degradation Quantization (signal) Syntactics Robustness Hardware entropy coding entropy

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What's your sign?: efficient sign coding for embedded wavelet image coding

What's your sign?: efficient sign coding for embedded wavele...

引用

Data Compression Conference (DCC)

作者： A. Deever S.S. Hemami Center for Applied Math Cornell University Ithaca NY USA School of Electrical Engineering Cornell University Ithaca NY USA

Wavelet transform coefficients are defined by both a magnitude and a sign. While promising algorithms exist for efficiently coding the transform coefficient magnitudes, current wavelet image coding algorithms are not efficient at coding the sign of the transform coefficients. It is generally assumed that there is no compression gain to be obtained from entropy coding of the sign. Only recently have some authors begun to investigate this component of wavelet image coding. In this paper, sign coding is examined in detail in the context of an embedded wavelet image coder. It is shown that PSNR improvements of up to 0.7 dB are possible from an efficient modeling and entropy coding of the coefficient signs, combined with a new extrapolation technique, which is used to improve the final estimate of insignificant coefficients. These sign coding techniques are applicable to any genre (e.g., zero-tree, context-model) of the embedded wavelet image coder.

关键词： Image coding Wavelet transforms entropy coding Extrapolation Context modeling Compaction PSNR Codecs Frequency Wavelet analysis

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Operator Design Methodology and Implementation for H.264 entropy Encoder

Operator Design Methodology and Implementation for H.264 Ent...

引用

International Conference on Information Engineering and Computer Science (ICIECS)

作者： Ziyi Hu Kuilin Chen Xin'an Wang Key Laboratory of Integrated Microsystem Science & Engineering Applications Peking University Shenzhen China

Currently the ASIC applications such as multimedia processing require shorter time-to-market and higher performance. Furthermore, with the IC manufacturing technology developing continually, from transistor level to logic gate level, the size of standard cells in digital circuits is increasing correspondingly. New methodology should be proposed to meet the need for shorter time-to-market IC industry, and the requirement of advanced IC manufacturing technology. This paper proposed the concept and principle of operator design methodology, then focused on the entropy coding application by the reconfigurable operator and finally gave the synthesis data. The results show that compared with the hardware design at the same cost of resources, this methodology can obtain hardware of suitable performance with regular structure. What is more, it can improve the design speed efficiently.

关键词： entropy coding Hardware Clocks Application specific integrated circuits Design methodology

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Recent advances in object-based image compression

Recent advances in object-based image compression

引用

Data Compression Conference (DCC)

作者： M.S. Schmalz Center for Computer Vision and Visualization University of Florida Gainesville FL USA

Summary form only given. Image compression has progressed from pixel-level entropy coding to transform coding applied to fixed regions (e.g., JPEG-2K with rectangular blocks). Our interest is in substitutions applied to arbitrarily-shaped regions. For example, object-based compression (OBC) segments disjoint, contiguous image regions, and compactly approximates each region's boundary and content (e.g., represented by a codebook exemplar). When region boundaries closely approximate scene object boundaries, OBC resembles object recognition. Disadvantages include cost of segmentation and region boundary representation, and pixel- or object-level distortion in the decompressed image.

关键词： Image coding Image segmentation Pixel Chromium Layout Computer vision Visualization entropy coding Transform coding Object recognition

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Towards Model-based Transrating of H.264 coded video

Towards Model-based Transrating of H.264 coded video

引用

IEEE Convention of the Electrical and ELectronic Engineers in Israel

作者： Naama Hait David Malah Department of Electrical Engineering Technion-Israel Institute of Technology Haifa Israel

A common approach for video transrating (bit rate reduction) is to requantize the transform coefficients. Optimal requantization aims to find a set of new step-sizes that achieve the target bit rate while introducing minimal distortion. Since the state of the art H.264 standard coder constrains requantization by limiting the amount of change in the quantization step-size from one macroblock to the next, the common Lagrangian optimization approach cannot be applied. We propose a solution to this dependency problem by extending each Lagrangian iteration with a constrained dynamic programming stage. Further, in order to reduce the computational load of evaluating the rate and distortion at each macroblock for multiple step-sizes, we suggest analytic models that can be applied for this purpose. The developed models are suitable for requantization and are matched to the context-adaptive entropy coding used in H.264. The proposed algorithm performs the requantization in the compressed domain and currently supports inter coded frames only. It reduces the run-time by a factor of 4, as compared to the full exhaustive optimization, and achieves up to 1[dB] gain in PSNR, as compared to a simple one-pass algorithm.

关键词： Bit rate Lagrangian functions Code standards Quantization Constraint optimization Dynamic programming Rate distortion theory Context modeling entropy coding Runtime

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VQ index coding for high-fidelity medical image compression

VQ index coding for high-fidelity medical image compression

引用

IEEE International Conference on Image Processing

作者： Wen Jiang Xiaolin Wu Wai Yin Ng Department of Information Engineering Chinese University of Hong Kong New Territories Hong Kong China Department of Computer Science University of Western Ontario London ONT Canada

ISBN: (纸本)0818681837

In order to obtain the high-fidelity medical compressed images, a new compression scheme is proposed. Based on the stringent requirements on lossy medical image compression, we refine the context modeling for a given class of medical images and utilize the conditional entropy coding of the VQ index (CECOVI) scheme to code the MR head images. The experimental results show that the image-type-dependent CECOVI can achieve better rate-distortion performance than the state-of-art wavelet image coder SPIHT. This also implies that incorporating the conditional entropy coding strategy into the VQ process is an appropriate way for high-fidelity medical image compression.

关键词： Image coding Biomedical imaging Medical diagnostic imaging entropy coding Rate-distortion Space technology Medical services Image storage Application software Image reconstruction

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Color Image coding by using Inter-Color Correlation

Color Image Coding by using Inter-Color Correlation

引用

IEEE International Conference on Image Processing

作者： Xing San Hua Cai Jiang Li Department of Electronic Engineering and Information Science University of Science and Technology China Media Communication Group Microsoft Research Asia Beijing China

Inter-color correlation between the luminance component and chrominance components has been utilized for color image coding for years. However, the correlation has not been clearly analyzed. In this paper, we analyze the inter-color correlation and answer two questions related to color image coding: (1) what kind of inter-color correlation exists in color images after the discrete wavelet transform?; and, (2) how strong is it? This analysis helps us to find a most suitable inter-color context and eventually leads to a new embedded color image codec. By using the discovered inter-color context, significant performance improvement can be achieved when encoding chrominance components.

关键词： Image coding Image color analysis Discrete wavelet transforms Image analysis Codecs Asia Wavelet coefficients Information science Wavelet analysis entropy coding

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Distributed source coding without Slepian-Wolf compression

Distributed source coding without Slepian-Wolf compression

引用

IEEE International Symposium on Information Theory

作者： Yang Yang Zixiang Xiong Department of Electrical and Computer Engineering Texas A and M University College Station TX USA

ISBN: (纸本)9781424443123

Slepian-Wolf (SW) coding, which is concerned with separate near-lossless compression of correlated sources (with joint decoding), forms the basis of distributed source coding (DSC) and can be used to exploit the correlation among quantized sources in lossy DSC problems such as Wyner-Ziv (WZ) coding and multiterminal (MT) source coding. However, SW coding is in general lossy, especially at short block length, and practical implementation is not nearly as well understood as entropy coding. This paper studies distributed source coding without SW coding. We employ entropy coding (after quantization if necessary) at each encoder while relying on joint estimation at the decoder to exploit the source correlation. We start from the simple lossless case before giving single-letter characterizations of the rate-distortion function for WZ coding without SW compression, and achievable rate region for MT source coding without SW compression. Examples on the binary symmetric and quadratic Gaussian cases are given.

关键词： Source coding Decoding entropy coding Quantization Rate-distortion H infinity control Encoding Rate distortion theory Turning

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Lossless image coding by cellular neural networks with backward error propagation learning

Lossless image coding by cellular neural networks with backw...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： Keisuke Takizawa Seiya Takenouchi Hisashi Aomori Tsuyoshi Otake Mamoru Tanaka Ichiro Matsuda Susumu Itoh Department of Electrical Engineering Tokyo University of Science Noda Chiba Japan Department of Software Science Tamagawa University Machida Tokyo Japan Department of Information and Communication Sciences Sophia University Chiyoda Tokyo Japan

This paper proposes a novel hierarchical lossless image coding scheme using cellular neural network (CNN). The coding architecture of proposed method is composed of three steps: split, predict, and entropy coding. The coding performance of proposed method highly depends on that of CNN predictors. The resulting prediction errors are encoded by the adaptive arithmetic coder. To achieve the high coding efficiency, the type of space-variant CNN templates and their parameters are optimized to minimize the actual coding bits of prediction residuals by the minimum coding rate learning with backward error propagation. Experimental results in 21 kinds of standard grayscale test images show that the average coding rates of the proposed scheme is better than that of the conventional schemes.

关键词： Image coding Standards Context Context modeling entropy coding Prediction algorithms

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Packet loss concealment in baseline JPEG coded images

Packet loss concealment in baseline JPEG coded images

引用

IEEE Symposium on Advances in Digital Filtering and Signal Processing

作者： S. Shirani F. Kossentini R. Ward Department of Electrical and Computer Engineering University of British Columbia Vancouver BC Canada

Loss of coded data can affect a JPEG decoded image to a large extent, making concealment of errors caused by data loss an important issue. Reconstruction of JPEG coded images in an error-prone channel environment is investigated in this paper. First a method for estimating the missing DC coefficients of a JPEG coded image which is required for decoding the compressed image, is suggested and evaluated. As the effects of errors in estimating the missing DC value will appear as stripes across the image, a post-processing technique for removing such stripes is then developed. Finally the missing data is reconstructed by exploiting the correlation between adjacent blocks. A novel reconstruction technique which has a good performance in reconstruction of edges is proposed. A key contribution of our work is that, unlike in previously published reconstruction algorithms, differential encoding of the DC coefficients is assumed. Simulation results indicate that the performance of our algorithm is very good, even when many packets are lost during transmission of the JPEG coded image.

关键词： Decoding Transform coding Image reconstruction Image coding Discrete cosine transforms Reconstruction algorithms Computer errors Propagation losses Quantization entropy coding

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