Proceedings DCC '98 Data Compression Conference (Cat. No.98TB100225)最新文献_第5页

Successive coefficient refinement for embedded lossless image compression 连续系数细化嵌入无损图像压缩

Proceedings DCC '98 Data Compression Conference (Cat. No.98TB100225) Pub Date : 1998-03-30 DOI: 10.1109/DCC.1998.672262

C. Creusere

引用次数: 1

Parallel algorithms for multi-indexed recurrence relations with applications to DPCM image compression 多索引递归关系并行算法及其在DPCM图像压缩中的应用

Proceedings DCC '98 Data Compression Conference (Cat. No.98TB100225) Pub Date : 1998-03-30 DOI: 10.1109/DCC.1998.672326

Abdou Youssef

{"title":"Parallel algorithms for multi-indexed recurrence relations with applications to DPCM image compression","authors":"Abdou Youssef","doi":"10.1109/DCC.1998.672326","DOIUrl":"https://doi.org/10.1109/DCC.1998.672326","url":null,"abstract":"Summary form only given. DPCM decoding is essentially the computation of a 2-indexed scalar recurrence relation; the two indices are: the row and column positions of the pixels. Although several logarithmic-time parallel algorithms for solving 1-indexed recurrence relations have been designed, no work has been reported on multi-indexed recurrence relations. Considering the importance of fast DPCM decoding of imagery, parallel algorithms for solving multi-indexed recurrence relations merit serious study. We designed novel parallel algorithms for solving 2-indexed recurrence relations, and identified the parallel architectures best suited for them. We developed three approaches: index sequencing, index decoupling, and dimension shifting. To solve a 2-indexed relation in DPCM decoding of an n/spl times/n image, index sequencing breaks down the relation into a sequence of n 1-indexed scalar recurrence relations that must be solved one after another. Each relation is then solved by a parallel O(nlogn) time algorithm on an n-processor hypercube or partitionable bus. Thus, the n equations take O(nlogn) time on n processors. Index decoupling, applicable in a common case of DPCM, breaks the 2-indexed relation into n independent 1-indexed recurrence relations, which are then solved simultaneously in O(logn) parallel time, using n/sup 2/ processors configured as a hypercube or a mesh of partitionable buses.","PeriodicalId":191890,"journal":{"name":"Proceedings DCC '98 Data Compression Conference (Cat. No.98TB100225)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129539193","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: 2

LZRW1 without hashing LZRW1没有哈希

Proceedings DCC '98 Data Compression Conference (Cat. No.98TB100225) Pub Date : 1998-03-30 DOI: 10.1109/DCC.1998.672311

Y. Reznik

引用次数: 1

Efficient lossless coding of medical image volumes using reversible integer wavelet transforms 利用可逆整数小波变换对医学图像体进行高效无损编码

Proceedings DCC '98 Data Compression Conference (Cat. No.98TB100225) Pub Date : 1998-03-30 DOI: 10.1109/DCC.1998.672188

A. Bilgin, G. Zweig, M. Marcellin

引用次数: 41

Color image compression by stack-run-end coding 基于堆栈运行端编码的彩色图像压缩

Proceedings DCC '98 Data Compression Conference (Cat. No.98TB100225) Pub Date : 1998-03-30 DOI: 10.1109/DCC.1998.672319

Min-Jen Tsai

{"title":"Color image compression by stack-run-end coding","authors":"Min-Jen Tsai","doi":"10.1109/DCC.1998.672319","DOIUrl":"https://doi.org/10.1109/DCC.1998.672319","url":null,"abstract":"Summary form only given. We present a new wavelet based image coding algorithm for color image compression. The key renovation of this algorithm is based on a new context oriented information conversion for data compression. A small number of symbol sets were then designed to convert the information from the wavelet transform domain into a compact data structure for each subband. Unlike zerotree coding or its variations which utilize the intersubband relationship into its own data representation where hierarchical or parents-children dependency is performed, our work is a low complexity intrasubband based coding method which only addresses the information within the subband or combines the information across the subbands. The scheme works first by color space conversion, followed by uniform scalar quantization. A concise data structure which categorizes the quantized coefficients into (stack, run, end) data format is performed, where the raster scanning order for individual subband is the most common used method but predefined scanning order will also work. Compared with the standard stack-run coding, our method generalized the symbol representation and the extension of the symbol alphabets. The termination symbols which carry the zero value information towards the end of the subband or across the subbands till the end of the image help to speed up the decoding processes. Our experiment results show that our approach is very competitive to the refinement of zerotree type schemes.","PeriodicalId":191890,"journal":{"name":"Proceedings DCC '98 Data Compression Conference (Cat. No.98TB100225)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132587113","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

Adaptive-rate coding modulation system for digital image transmission 数字图像传输的自适应速率编码调制系统

Proceedings DCC '98 Data Compression Conference (Cat. No.98TB100225) Pub Date : 1998-03-30 DOI: 10.1109/DCC.1998.672294

J. Kleider, G. Abousleman

{"title":"Adaptive-rate coding modulation system for digital image transmission","authors":"J. Kleider, G. Abousleman","doi":"10.1109/DCC.1998.672294","DOIUrl":"https://doi.org/10.1109/DCC.1998.672294","url":null,"abstract":"Summary form only given. We propose two methods to provide optimal image quality at a fixed image delivery rate for any given transmission channel condition. The first method, channel-controlled variable-rate (CCVR) image coding, employs adaptive-rate source coding and channel coding, while operating with a fixed modulation symbol rate. The second method, adaptive-rate coding-modulation (ARCM), extends the CCVR system by utilizing adaptive modulation. Both methods use a variable-compression-ratio image coder and variable-rate channel coding. The objective is to maximize the quality of the reconstructed image at the receiver when transmitted through Rayleigh fading and additive white Gaussian noise (AWGN). The CCVR system maximizes the reconstructed image quality through a bit-rate trade-off between the source and channel coders. The ARCM method provides a trade-off between the rates of source and channel coding, and the modulation rate. Both methods require knowledge of the channel state which is used by the receiver to inform the transmitter, via a feedback channel, of the optimal strategy for image compression, channel coding, and modulation format. The resulting systems achieve up to a 17 dB improvement over the peak signal-to-noise ratio (PSNR) performance of a system using a fixed-compression-ratio image coder and fixed-rate channel coding. Reconstructed image quality is evaluated through both quantitative and subjective measures using peak signal-to-noise ratio and visual analysis, respectively.","PeriodicalId":191890,"journal":{"name":"Proceedings DCC '98 Data Compression Conference (Cat. No.98TB100225)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132109387","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

A memory-efficient adaptive Huffman coding algorithm for very large sets of symbols 一种适用于大量符号集的高效记忆自适应霍夫曼编码算法

Proceedings DCC '98 Data Compression Conference (Cat. No.98TB100225) Pub Date : 1998-03-30 DOI: 10.1109/DCC.1998.672310

S. Pigeon, Yoshua Bengio

{"title":"A memory-efficient adaptive Huffman coding algorithm for very large sets of symbols","authors":"S. Pigeon, Yoshua Bengio","doi":"10.1109/DCC.1998.672310","DOIUrl":"https://doi.org/10.1109/DCC.1998.672310","url":null,"abstract":"Summary form only given. The problem of computing the minimum redundancy codes as we observe symbols one by one has received a lot of attention. However, existing algorithms implicitly assumes that either we have a small alphabet or that we have an arbitrary amount of memory at our disposal for the creation of a coding tree. In real life applications one may need to encode symbols coming from a much larger alphabet, for e.g. coding integers. We introduce a new algorithm for adaptive Huffman coding, called algorithm M, that uses space proportional to the number of frequency classes. The algorithm uses a tree with leaves that represent sets of symbols with the same frequency, rather than individual symbols. The code for each symbol is therefore composed of a prefix (specifying the set, or the leaf of the tree) and a suffix (specifying the symbol within the set of same-frequency symbols). The algorithm uses only two operations to remain as close as possible to the optimal: set migration and rebalancing. We analyze the computational complexity of algorithm M, and point to its advantages in terms of low memory complexity and fast decoding. Comparative experiments were performed with algorithm M on the Calgary corpus, with static Huffman coding as well as with another adaptive Huffman coding algorithms, algorithm /spl Lambda/ of Vitter. Experiments show that M performs comparably or better than the other algorithms but requires much less memory. Finally, we present an improved algorithm, M/sup +/, for non-stationary data, which models the distribution of the data in a fixed-size window in the data sequence.","PeriodicalId":191890,"journal":{"name":"Proceedings DCC '98 Data Compression Conference (Cat. No.98TB100225)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132234454","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: 13

Codeword assignment for fixed-length entropy coded video streams 定长熵编码视频流的码字分配

Proceedings DCC '98 Data Compression Conference (Cat. No.98TB100225) Pub Date : 1998-03-30 DOI: 10.1109/DCC.1998.672155

Ramon Llados-Bernaus, R. Stevenson

引用次数: 1

Correcting English text using PPM models 使用PPM模型校正英文文本

Proceedings DCC '98 Data Compression Conference (Cat. No.98TB100225) Pub Date : 1998-03-30 DOI: 10.1109/DCC.1998.672157

W. Teahan, S. Inglis, J. Cleary, Geoffrey Holmes

引用次数: 30

Improved lossless halftone image coding using a fast adaptive context template selection scheme 改进的无损半色调图像编码使用快速自适应上下文模板选择方案

Proceedings DCC '98 Data Compression Conference (Cat. No.98TB100225) Pub Date : 1998-03-30 DOI: 10.1109/DCC.1998.672265

K. Denecker, P. Neve, I. Lemahieu

引用次数: 3