Proceedings DCC 2000. Data Compression Conference最新文献_第2页

Exploiting interframe redundancies in the lossless compression of 3D medical images 利用帧间冗余在无损压缩的三维医学图像

Proceedings DCC 2000. Data Compression Conference Pub Date : 2000-03-28 DOI: 10.1109/DCC.2000.838222

S. V. Assche, D. D. Rycke, W. Philips, I. Lemahieu

{"title":"Exploiting interframe redundancies in the lossless compression of 3D medical images","authors":"S. V. Assche, D. D. Rycke, W. Philips, I. Lemahieu","doi":"10.1109/DCC.2000.838222","DOIUrl":"https://doi.org/10.1109/DCC.2000.838222","url":null,"abstract":"Summary form only given. An evaluation is made of different approaches to removing interframe redundancies. The test images we used are the MRI and CT images available from the Visual Human Project. Firstly, we found that linear predictive techniques are not able to provide any compression improvement. Even an optimal linear predictor (least-squares optimization), which holds pixels from the current and the previous frames, does not outperform the very simple 2D lossless JPEG predictor number 7. However nonlinear techniques, such as context-modeling do yield better results. In a simple experiment, lossless JPEG was estimated to code intraframe prediction errors using an interframe context. The context for coding the current pixel is formed by the magnitude of the prediction error of the corresponding pixel in the previous frame. Note that this prediction error comes from the intraframe prediction step in the previous frame. Using this interframe context-modeling approach, a reduction of the bit rate of up to 1 bit per pixel is obtainable. It is obvious that the context serves as an edge-detector, albeit a very simple and straightforward one. A new technique is proposed based on the 2D lossless image compressor JPEG-LS. The existing context-modeling scheme is extended to also catch the interframe redundancies. The interframe context is very similar to the abovementioned one, however the sign of the prediction error in the previous frame is also used.","PeriodicalId":218804,"journal":{"name":"Proceedings DCC 2000. Data Compression Conference","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124756043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 20

Product code and recurrent alternative decoding for wireless image transmission 用于无线图像传输的产品编码和循环替代解码

Proceedings DCC 2000. Data Compression Conference Pub Date : 2000-03-28 DOI: 10.1109/DCC.2000.838194

Lei Cao, C. Chen

{"title":"Product code and recurrent alternative decoding for wireless image transmission","authors":"Lei Cao, C. Chen","doi":"10.1109/DCC.2000.838194","DOIUrl":"https://doi.org/10.1109/DCC.2000.838194","url":null,"abstract":"Summary form only given. We have developed a novel channel coding scheme for image transmission over wireless channels. A key component of this scheme is the construction of the product code using a convolutional code and a recursive systematic code (RSC) in the horizontal and vertical directions, respectively. High performance transmission has been achieved through an innovative recurrent alternative decoding scheme based on constrained Viterbi decoding. We used RSC because of its systematic structure so that we did not need to transmit the original data portion of the RSC coding outcome since this portion can be obtained from the other direction of channel decoding. At the receiving end, the data will at first be decoded along the horizontal direction. After decoding, the position of a correctly decoded row will be assigned a positive sign and be preserved. When we decode along the vertical direction, the positive signs after horizontal decoding will be used as constraints in the Viterbi decoding algorithm to force the survival path's passing through these known positions of correctly decoded bits. The constrained Viterbi algorithm using known correct bits enables us to derive likely correct values for other bits. This reduces greatly possible paths along the trellis diagram even though some or the paths dropped may have smaller path cost due to channel noise corruption and would otherwise be preserved by the unconstrained Viterbi algorithm. Moreover, this also reduces significantly the comparisons between the branches and the received symbols. Similarly the use of the correctly localized columns are also preserved and used again to refine the next round of horizontal decoding. Such recurrent decoding will alternate between horizontal and vertical directions until all data is correctly decoded or until there is no more improvement in both directions. We investigated the performance of the proposed scheme for both BSC and GEC channels and report the results here.","PeriodicalId":218804,"journal":{"name":"Proceedings DCC 2000. Data Compression Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130462619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fast progressive image coding without wavelets 无小波的快速渐进图像编码

Proceedings DCC 2000. Data Compression Conference Pub Date : 2000-03-28 DOI: 10.1109/DCC.2000.838164

Henrique S. Malvar

引用次数: 82

Lossless compression of high-volume numerical data from simulations 来自模拟的大量数值数据的无损压缩

Proceedings DCC 2000. Data Compression Conference Pub Date : 2000-03-28 DOI: 10.1109/DCC.2000.838221

V. Engelson, D. Fritzson, P. Fritzson

引用次数: 95

An efficient successive elimination algorithm for block-matching motion estimation 一种高效的块匹配运动估计逐次消去算法

Proceedings DCC 2000. Data Compression Conference Pub Date : 2000-03-28 DOI: 10.1109/DCC.2000.838206

H. Mahmoud, M. Bayoumi

{"title":"An efficient successive elimination algorithm for block-matching motion estimation","authors":"H. Mahmoud, M. Bayoumi","doi":"10.1109/DCC.2000.838206","DOIUrl":"https://doi.org/10.1109/DCC.2000.838206","url":null,"abstract":"Summary form only given. Low power VLSI video compression processors are in high demand for the emerging wireless video applications. Video compression processors include VLSI implementation of a motion estimation algorithm. Many motion estimation algorithms are found in the literature. Some of them are fast but cannot guarantee an optimal solution; they can be stuck in local optima. Such algorithms are fast, consumes less power when implemented in VLSI, but they can result in high levels of distortion that cannot be accepted in many applications. On the other hand the full search block matching algorithm (FSBM) is computationally intensive and a VLSI implementation of such an algorithm has high power consumption. This paper presents an exhaustive search algorithm for block matching motion estimation. The proposed algorithm reduces the computational load with successive elimination of non-candidate blocks in the search window. Our proposed algorithm assigns each pixel to a category depending on its value. The number of categories is predetermined. The algorithm consists of number of stages, the first of which has the fewer categories, eliminating those search points that are the farthest from the match. The last stage is the FSBM but with fewer search points. This computational reduction leads to low-power VLSI implementation of the algorithm. Also, it leads to faster efficient motion estimation procedure. The correctness of this algorithm and its complexity are proved.","PeriodicalId":218804,"journal":{"name":"Proceedings DCC 2000. Data Compression Conference","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122714866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Parallel Huffman decoding 并行霍夫曼解码

Proceedings DCC 2000. Data Compression Conference Pub Date : 2000-03-28 DOI: 10.1109/DCC.2000.838178

S. T. Klein, Y. Wiseman

引用次数: 25

Coding of image residuals with tailbiting convolutional codes and BCJR decoding 图像残差尾部卷积编码与BCJR解码

Proceedings DCC 2000. Data Compression Conference Pub Date : 2000-03-28 DOI: 10.1109/DCC.2000.838214

M. Novak

引用次数: 0

Group testing for image compression 图像压缩组试验

Proceedings DCC 2000. Data Compression Conference Pub Date : 2000-03-28 DOI: 10.1109/DCC.2000.838140

E. S. Hong, R. Ladner

引用次数: 112

Content layer progressive coding of digital maps 数字地图的内容层递进编码

Proceedings DCC 2000. Data Compression Conference Pub Date : 2000-03-28 DOI: 10.1109/DCC.2000.838163

Søren Forchhammer, O. Jensen

引用次数: 24

Wireless image transmission using multiple-description based concatenated codes 使用基于多重描述的连接代码的无线图像传输

Proceedings DCC 2000. Data Compression Conference Pub Date : 2000-03-28 DOI: 10.1117/12.382963

D. Sachs, Anand Raghavan, K. Ramchandran

{"title":"Wireless image transmission using multiple-description based concatenated codes","authors":"D. Sachs, Anand Raghavan, K. Ramchandran","doi":"10.1117/12.382963","DOIUrl":"https://doi.org/10.1117/12.382963","url":null,"abstract":"Summary form only given. This work introduces a multiple-description product code which aims at optimally generating multiple, equally-important wavelet image descriptions from an image encoded by the popular SPIHT image coder. Because the SPIHT image coder is highly sensitive to errors, forward error correction is used to protect the image against bit errors occurring in the channel. The error-correction code is a concatenated channel code including a row (outer) code based on RCPC codes with CRC error detection and a source-channel column (inner) code consisting of the scalable SPIHT image coder and an optimized array of unequal protection Reed-Solomon erasure-correction codes. By matching the unequal protection codes to the embedded source bitstream using our simple, fast optimizer, we maximize expected image quality and provide for graceful degradation of the received image during fades. To achieve unequal protection, each packet is split into many Reed-Solomon symbols. The i/sup th/ symbol in each packet forms an (n,k) Reed-Solomon code or \"column\". A fast, nearly-optimal optimizer, based on Lagrange multipliers and optimal to within convex hull and discretization approximations, chooses k for each Reed-Solomon \"column\" to minimize the expected mean-square error at the receiver. We validated our use of this structure by evaluating its performance in the context of transmitting images over a wireless fading channel. The performance of this scheme was evaluated by simulating the transmission of the Lena image over a Clarke flat-fading channel with an average SNR of 10 dB and a normalized Doppler frequency of 10/sup -5/ Hz.","PeriodicalId":218804,"journal":{"name":"Proceedings DCC 2000. Data Compression Conference","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116319653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 130