2007 Data Compression Conference (DCC'07)最新文献

{"title":"Memory-Efficient Decoding of Variable Length Codes for Monotonic Sources","authors":"Y. Reznik","doi":"10.1109/DCC.2007.54","DOIUrl":"https://doi.org/10.1109/DCC.2007.54","url":null,"abstract":"This paper presents variable length code and its corresponding Moffatt-Turpin decoding structure. The code of a modified algorithm using such data structure.","PeriodicalId":234035,"journal":{"name":"2007 Data Compression Conference (DCC'07)","volume":"125 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122909529","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}

{"title":"Nonuniform Compression in Databases with Haar Wavelet","authors":"Su Chen, A. Nucci","doi":"10.1109/DCC.2007.59","DOIUrl":"https://doi.org/10.1109/DCC.2007.59","url":null,"abstract":"Data synopsis is a lossy compressed representation of data stored into databases that helps the query optimizer to speed up the query process, e.g. time to retrieve the data from the database. An efficient data synopsis must provide accurate information about the distribution of data to the query optimizer at any point in time. Due to the fact that some data will be queried more often than others, a good data synopsis should consider the use of nonuniform accuracy, e.g. provide better approximation of data that are queried the most. Although, the generation of data synopsis is a critical step to achieve a good approximation of the initial data representation, data synopsis must be updated over time when dealing with time varying data. In this paper, we introduce new Haar wavelet synopses for nonuniform accuracy and time-varying data that can be generated in linear time and space, and updated in sublinear time. The efficiency of our new data synopses is validated against other linear methods by using both synthetic and real data sets","PeriodicalId":234035,"journal":{"name":"2007 Data Compression Conference (DCC'07)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129073506","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}

{"title":"VLR-Based Optimal Positioning of Resynchronization Markers","authors":"Yong Fang, Jechang Jeong","doi":"10.1109/DCC.2007.80","DOIUrl":"https://doi.org/10.1109/DCC.2007.80","url":null,"abstract":"Resynchronization makers (RM) are widely used in variable-length coding (VLC) bit stream to limit error propagation. However, the insertion of RMs introduces some decrease in coding efficiency unavoidably. To make a compromise between coding efficiency and error-resilience, this poster proposes a novel approach to the optimal RM positioning in which the valid-length ratio (VLR) is used as the measure of information. Hence, the optimization problem is converted into maximizing the VLR under a certain channel conditions","PeriodicalId":234035,"journal":{"name":"2007 Data Compression Conference (DCC'07)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127663454","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}

{"title":"Interference Multispectral Image Compression with Adaptive Distortion Control in Fourier Domain","authors":"Jing Ma, Chengke Wu, Dong Chen, Jie Guo","doi":"10.1109/DCC.2007.49","DOIUrl":"https://doi.org/10.1109/DCC.2007.49","url":null,"abstract":"The interferential spectrometer is considered as the next generation of imaging spectrometers in aerial remote sensing. The customary multispectral images compression methods only consider the quality of reconstructed images in spatial domain without concerning the effect in Fourier domain where the application of spectrum is often used, such as substance classification and recognition. Our method WRDO-SPIHT (weighted rate-distortion optimization for SPIHT) is proposed based on the relationship between the distortion in Fourier domain and compression in spatial domain.","PeriodicalId":234035,"journal":{"name":"2007 Data Compression Conference (DCC'07)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116283634","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}

{"title":"A Content-based Robust Mode Decision Scheme for Internet Videophone Applications","authors":"Jin Xu, Limin Sun, Zhimei Wu","doi":"10.1109/DCC.2007.1","DOIUrl":"https://doi.org/10.1109/DCC.2007.1","url":null,"abstract":"In this paper, a content-based error resilient RDO mode decision scheme is proposed for Internet videophone applications. The experimental results based on typical head-and-shoulder video sequences under common Internet channel condition show that, comparing with conventional error resilient RDO mode decision schemes, the proposed mode decision scheme improves the average luminance PSNR of visually important foreground area consistently regardless of the packet loss rate.","PeriodicalId":234035,"journal":{"name":"2007 Data Compression Conference (DCC'07)","volume":"273 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125708452","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}

{"title":"Algorithms and Hardware Structures for Unobtrusive Real-Time Compression of Instruction and Data Address Traces","authors":"M. Milenkovic, A. Milenković, Martin Burtscher","doi":"10.1109/DCC.2007.10","DOIUrl":"https://doi.org/10.1109/DCC.2007.10","url":null,"abstract":"Instruction and data address traces are widely used by computer designers for quantitative evaluations of new architectures and workload characterization, as well as by software developers for program optimization, performance tuning, and debugging. Such traces are typically very large and need to be compressed to reduce the storage, processing, and communication bandwidth requirements. However, preexisting general-purpose and trace-specific compression algorithms are designed for software implementation and are not suitable for runtime compression. Compressing program execution traces at runtime in hardware can deliver insights into the behavior of the system under test without any negative interference with normal program execution. Traditional debugging tools, on the other hand, have to stop the program frequently to examine the state of the processor. Moreover, software developers often do not have access to the entire history of computation that led to an erroneous state. In addition, stepping through a program is a tedious task and may interact with other system components in such a way that the original errors disappear, thus preventing any useful insight. The need for unobtrusive tracing is further underscored by the development of computer systems that feature multiple processing cores on a single chip. In this paper, we introduce a set of algorithms for compressing instruction and data address traces that can easily be implemented in an on-chip trace compression module and describe the corresponding hardware structures. The proposed algorithms are analytically and experimentally evaluated. Our results show that very small hardware structures suffice to achieve a compression ratio similar to that of a software implementation of gzip while being orders of magnitude faster. A hardware structure with slightly over 2 KB of state achieves a compression ratio of 125.9 for instruction address traces, whereas gzip achieves a compression ratio of 87.4. For data address traces, a hardware structure with 5 KB of state achieves a compression ratio of 6.1, compared to 6.8 achieved by gzip","PeriodicalId":234035,"journal":{"name":"2007 Data Compression Conference (DCC'07)","volume":"133 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130632066","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}

{"title":"The Model based Similarity Metric","authors":"L. Gueguen, M. Datcu","doi":"10.1109/DCC.2007.76","DOIUrl":"https://doi.org/10.1109/DCC.2007.76","url":null,"abstract":"This paper addresses the problem of building a compact representation of objects which enables to define a similarity measure. The key idea is to provide a mean to extract and represent the relevant information of an object. By integrating the minimum length description to an informational similarity metric, a new informational measure is proposed based on models. First, we make the strong assumption that for any object x there exists a model Mx such that K(x) = K(x | M x) + K(Mx)","PeriodicalId":234035,"journal":{"name":"2007 Data Compression Conference (DCC'07)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131959521","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}

{"title":"Compression of a Set of Strings","authors":"J. Lánský, M. Zemlicka","doi":"10.1109/DCC.2007.25","DOIUrl":"https://doi.org/10.1109/DCC.2007.25","url":null,"abstract":"Dictionary is used by many compression methods. Some of them put the dictionary into the compressed message. In such cases the improvements in dictionary compression can improve the performance of the compression methods. We have focused on compression of dictionaries of words or syllables. The dictionary compression is often based on tree representation of the dictionary. We suppose that proper encoding of the tree can save a lot of space. We have therefore focused on minimizing the stored information corresponding to a tree node. We store only the number of children encoded by Elias gamma code, the difference of encoded character from the left sibling encoded by Elias delta code, and the information whether given node represents a dictionary item stored in a single bit. The distance from left brother is skipped for the root and the information whether the node represents a dictionary item is skipped by the leaves.","PeriodicalId":234035,"journal":{"name":"2007 Data Compression Conference (DCC'07)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133580560","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}

{"title":"Quantization of Sparse Representations","authors":"P. Boufounos, Richard Baraniuk","doi":"10.1109/DCC.2007.68","DOIUrl":"https://doi.org/10.1109/DCC.2007.68","url":null,"abstract":"Compressive sensing (CS) is a new signal acquisition technique for sparse and compressible signals. Rather than uniformly sampling the signal, CS computes inner products with randomized basis functions; the signal is then recovered by a convex optimization. Random CS measurements are universal in the sense that the same acquisition system is sufficient for signals sparse in any representation. This paper examines the quantization of strictly sparse, power-limited signals and concludes that CS with scalar quantization uses its allocated rate inefficiently. The results complement related work on the quantization of CS measurements of compressible signals.","PeriodicalId":234035,"journal":{"name":"2007 Data Compression Conference (DCC'07)","volume":"220 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130398608","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}

{"title":"A Parallel Decoder for Lossless Image Compression by Block Matching","authors":"L. Cinque, S. Agostino","doi":"10.1109/DCC.2007.6","DOIUrl":"https://doi.org/10.1109/DCC.2007.6","url":null,"abstract":"A work-optimal O(lognlogM) time PRAM-EREW algorithm for lossless image compression by block matching was shown in L. Cinque et al., (2003), where n is the size of the image and M is the maximum size of the match. The design of a parallel decoder was left as an open problem. By slightly modifying the parallel encoder, in this paper we show how to implement the decoder in O(lognlogM) time with O(n/logn) processors on the PRAM-EREW. With the realistic assumption that the size of the compressed image is O(n1/2), the parallel decoder requires O(log2n) time and O(n/logn) processors on the mesh of trees","PeriodicalId":234035,"journal":{"name":"2007 Data Compression Conference (DCC'07)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132432240","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}