[Summary form only given]. We introduce a motion wavelet transform zero tree (WZT) codec which achieves good compression ratios and can be implemented in a single ASIC of modest size. The codec employs a group of pictures (GOP) of two interlaced video frames, edge filters for the boundaries, intermediate field image compression and block compression structure. Specific features of the implementation for a small single chip are: 1) Transform filters are short and use dyadic rational coefficients with small numerators. Implementation can be accomplished with adds and shifts. We propose a Mallat pyramid resulting from five filter applications in the horizontal direction and three applications in the vertical direction. We use modified edge filters near block and image boundaries so as to utilize actual image values. 2) Motion image compression is used in place of motion compensation. We have applied transform compression in the temporal direction to a GOP of four fields. A two level temporal Mallat pyramid is used as a tensor product with the spatial pyramid. The linear edge filters are used at the fine level and the modified Haar filters at the coarse level, resulting in four temporal subbands. 3) Processing can be decoupled into the processing of blocks of 8 scan lines of 32 pixels each. This helps reduce the RAM requirements to the point that the RAM can be placed in the ASIC itself. 4) Quantization denominators are powers of two, enabling implementation by shifts. 5) Zero-tree coding yields a progressive encoding which is easily rate controlled. 6) The codec itself imposes a very low delay of less than 3.5 ms within a field and 67 ms for a GOP. The overall conclusion is that it is reasonable to expect that this method can be implemented, including memory, in a few mm/sup 2/ of silicon.
{"title":"A fractional chip wavelet zero tree codec (WZT) for video compression","authors":"K. Kolarov, W. Lynch, Bill Arrighi, Bob Hoover","doi":"10.1109/DCC.1999.785692","DOIUrl":"https://doi.org/10.1109/DCC.1999.785692","url":null,"abstract":"[Summary form only given]. We introduce a motion wavelet transform zero tree (WZT) codec which achieves good compression ratios and can be implemented in a single ASIC of modest size. The codec employs a group of pictures (GOP) of two interlaced video frames, edge filters for the boundaries, intermediate field image compression and block compression structure. Specific features of the implementation for a small single chip are: 1) Transform filters are short and use dyadic rational coefficients with small numerators. Implementation can be accomplished with adds and shifts. We propose a Mallat pyramid resulting from five filter applications in the horizontal direction and three applications in the vertical direction. We use modified edge filters near block and image boundaries so as to utilize actual image values. 2) Motion image compression is used in place of motion compensation. We have applied transform compression in the temporal direction to a GOP of four fields. A two level temporal Mallat pyramid is used as a tensor product with the spatial pyramid. The linear edge filters are used at the fine level and the modified Haar filters at the coarse level, resulting in four temporal subbands. 3) Processing can be decoupled into the processing of blocks of 8 scan lines of 32 pixels each. This helps reduce the RAM requirements to the point that the RAM can be placed in the ASIC itself. 4) Quantization denominators are powers of two, enabling implementation by shifts. 5) Zero-tree coding yields a progressive encoding which is easily rate controlled. 6) The codec itself imposes a very low delay of less than 3.5 ms within a field and 67 ms for a GOP. The overall conclusion is that it is reasonable to expect that this method can be implemented, including memory, in a few mm/sup 2/ of silicon.","PeriodicalId":103598,"journal":{"name":"Proceedings DCC'99 Data Compression Conference (Cat. No. PR00096)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133553667","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}
Implementation of variable-length code (VLC) decoders can involve a tradeoff between the number of decoding steps and memory usage. In this paper, we proposed a novel scheme for optimizing this tradeoff using a machine model abstracted from general purpose processors with hierarchical memories. We formulate the VLC decode problem as an optimization problem where the objective is to minimize the average decoding time. After showing that the problem is NP-complete, we present a Lagrangian algorithm that finds an approximate solution with bounded error. An implementation is automatically synthesized by a code generator. To demonstrate the efficacy of our approach, we conducted experiments of decoding codebooks for a pruned tree-structured vector quantizer and H.263 motion vector that show a performance gain of our proposed algorithm over single table lookup implementation and logic implementation.
{"title":"Software synthesis of variable-length code decoder using a mixture of programmed logic and table lookups","authors":"Gene Cheung, S. McCanne, C. Papadimitriou","doi":"10.1109/DCC.1999.755661","DOIUrl":"https://doi.org/10.1109/DCC.1999.755661","url":null,"abstract":"Implementation of variable-length code (VLC) decoders can involve a tradeoff between the number of decoding steps and memory usage. In this paper, we proposed a novel scheme for optimizing this tradeoff using a machine model abstracted from general purpose processors with hierarchical memories. We formulate the VLC decode problem as an optimization problem where the objective is to minimize the average decoding time. After showing that the problem is NP-complete, we present a Lagrangian algorithm that finds an approximate solution with bounded error. An implementation is automatically synthesized by a code generator. To demonstrate the efficacy of our approach, we conducted experiments of decoding codebooks for a pruned tree-structured vector quantizer and H.263 motion vector that show a performance gain of our proposed algorithm over single table lookup implementation and logic implementation.","PeriodicalId":103598,"journal":{"name":"Proceedings DCC'99 Data Compression Conference (Cat. No. PR00096)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132572314","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}
[Summary form only given] Typically, the lossless compression of color images is achieved by separately compressing the three RGB monochromatic image components. The proposed method takes into account the fact that high spatial correlations exist not only within each monochromatic frame but also between similar spatial locations in adjacent monochromatic frames. Based on the observation that the prediction errors produced by the JPEG predictor in each RGB monochromatic frame present very similar structures, we propose two new chromatic predictors, called chromatic differential predictor (CDP) and classified CDP (CCDP), to capture the spectral dependencies between the monochromatic frames. In addition to prediction schemes, we consider context modeling schemes that take into account the prediction errors in spatially and/or spectrally adjacent pixels in order to efficiently encode the prediction errors. In order to demonstrate the advantage of the proposed lossless color image compression scheme, 5 different types of images are selected from the KODAK image set. All images are RGB 24 bpp color images with resolution 768/spl times/512. The experimental results demonstrate significant improvement in compression performance. Its fast implementation and high compression ratio may be a promising approach for the application of real-time color video compression.
{"title":"Lossless color image compression using chromatic correlation","authors":"Wen Jiang, L. Bruton","doi":"10.1109/DCC.1999.785690","DOIUrl":"https://doi.org/10.1109/DCC.1999.785690","url":null,"abstract":"[Summary form only given] Typically, the lossless compression of color images is achieved by separately compressing the three RGB monochromatic image components. The proposed method takes into account the fact that high spatial correlations exist not only within each monochromatic frame but also between similar spatial locations in adjacent monochromatic frames. Based on the observation that the prediction errors produced by the JPEG predictor in each RGB monochromatic frame present very similar structures, we propose two new chromatic predictors, called chromatic differential predictor (CDP) and classified CDP (CCDP), to capture the spectral dependencies between the monochromatic frames. In addition to prediction schemes, we consider context modeling schemes that take into account the prediction errors in spatially and/or spectrally adjacent pixels in order to efficiently encode the prediction errors. In order to demonstrate the advantage of the proposed lossless color image compression scheme, 5 different types of images are selected from the KODAK image set. All images are RGB 24 bpp color images with resolution 768/spl times/512. The experimental results demonstrate significant improvement in compression performance. Its fast implementation and high compression ratio may be a promising approach for the application of real-time color video compression.","PeriodicalId":103598,"journal":{"name":"Proceedings DCC'99 Data Compression Conference (Cat. No. PR00096)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134580337","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}
The SPIHT algorithm is shown to implicitly use quadtree-based classification. The rate-distortion encoding performance of the classes is described, and quantization improvements presented. A new encoding algorithm combines a general SPIHT data structure with the granular gain of multi-dimensional quantization to achieve improved PSNR versus rate performance.
{"title":"Quadtree classification and TCQ image coding","authors":"B. A. Banister, T. Fischer","doi":"10.1109/DCC.1999.755664","DOIUrl":"https://doi.org/10.1109/DCC.1999.755664","url":null,"abstract":"The SPIHT algorithm is shown to implicitly use quadtree-based classification. The rate-distortion encoding performance of the classes is described, and quantization improvements presented. A new encoding algorithm combines a general SPIHT data structure with the granular gain of multi-dimensional quantization to achieve improved PSNR versus rate performance.","PeriodicalId":103598,"journal":{"name":"Proceedings DCC'99 Data Compression Conference (Cat. No. PR00096)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127163168","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}
Summary form only given. We present an architecture for digital HDTV video decoding (MPEG-2 MP@HL), based on dual decoding data paths controlled in a block layer synchronization manner and an efficient write back scheme. Our fixed schedule controller synchronizes the baseline units on a block basis in both data-paths. This scheme reduces embedded buffer sizes within the decoder and eliminates a lot of external memory bus contentions. In our write back scheme, the display DRAM is physically separated from the anchor picture DRAM, and is added to the display engine, not to the bus. The slight increase in overall DRAM size is acceptable due to the low DRAM cost today. This improves the parallelism in accessing anchor and display pictures and saves about 80 clock cycles per macroblock (based on a 81 MHz clock). Compared to the other decoding approaches such as the slice bar decoding method and the crossing-divided method, this scheme reduces memory access contentions and the amount of embedded local memory required. Our simulations show that with a relatively low speed 81 MHz clock, our architecture uses fewer than the 332 cycles (required real-time decoding upper bound), to decode each macroblock, without a high cost in overall chip area.
{"title":"A novel dual-path architecture for HDTV video decoding","authors":"N. Wang, N. Ling","doi":"10.1109/DCC.1999.785714","DOIUrl":"https://doi.org/10.1109/DCC.1999.785714","url":null,"abstract":"Summary form only given. We present an architecture for digital HDTV video decoding (MPEG-2 MP@HL), based on dual decoding data paths controlled in a block layer synchronization manner and an efficient write back scheme. Our fixed schedule controller synchronizes the baseline units on a block basis in both data-paths. This scheme reduces embedded buffer sizes within the decoder and eliminates a lot of external memory bus contentions. In our write back scheme, the display DRAM is physically separated from the anchor picture DRAM, and is added to the display engine, not to the bus. The slight increase in overall DRAM size is acceptable due to the low DRAM cost today. This improves the parallelism in accessing anchor and display pictures and saves about 80 clock cycles per macroblock (based on a 81 MHz clock). Compared to the other decoding approaches such as the slice bar decoding method and the crossing-divided method, this scheme reduces memory access contentions and the amount of embedded local memory required. Our simulations show that with a relatively low speed 81 MHz clock, our architecture uses fewer than the 332 cycles (required real-time decoding upper bound), to decode each macroblock, without a high cost in overall chip area.","PeriodicalId":103598,"journal":{"name":"Proceedings DCC'99 Data Compression Conference (Cat. No. PR00096)","volume":"2007 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127300052","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}
Signal representations based on low-resolution quantization of redundant expansions is an interesting source coding paradigm, the most important practical case of which is oversampled A/D conversion. Signal reconstruction from quantized coefficients of a redundant expansion and accuracy of representations of this kind are problems which are still not well understood and these are studied in this paper in finite dimensional spaces. It has been previously proven that accuracy of signal representations based on quantized redundant expansions, measured as the squared Euclidean norm of the reconstruction error, cannot be better than O(1/(r/sup 2/)), where r is the expansion redundancy. We give some general conditions under which 1/(r/sup 2/) accuracy can be attained. We also suggest a form of structure for overcomplete families which facilitates reconstruction, and which enables efficient encoding of quantized coefficients with a logarithmic increase of the bit-rate in redundancy.
{"title":"Source coding with quantized redundant expansions: accuracy and reconstruction","authors":"Z. Cvetković","doi":"10.1109/DCC.1999.755684","DOIUrl":"https://doi.org/10.1109/DCC.1999.755684","url":null,"abstract":"Signal representations based on low-resolution quantization of redundant expansions is an interesting source coding paradigm, the most important practical case of which is oversampled A/D conversion. Signal reconstruction from quantized coefficients of a redundant expansion and accuracy of representations of this kind are problems which are still not well understood and these are studied in this paper in finite dimensional spaces. It has been previously proven that accuracy of signal representations based on quantized redundant expansions, measured as the squared Euclidean norm of the reconstruction error, cannot be better than O(1/(r/sup 2/)), where r is the expansion redundancy. We give some general conditions under which 1/(r/sup 2/) accuracy can be attained. We also suggest a form of structure for overcomplete families which facilitates reconstruction, and which enables efficient encoding of quantized coefficients with a logarithmic increase of the bit-rate in redundancy.","PeriodicalId":103598,"journal":{"name":"Proceedings DCC'99 Data Compression Conference (Cat. No. PR00096)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128812773","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}
Summary form only given. In order to limit error propagation, we divide the topological data of the entire mesh into several segments. Each segment is identified by its synchronization word and header. Due to the use of the arithmetic coder, data of a whole segment would often become useless in the presence of even a single bit error. Furthermore, several adjacent segments may be corrupted simultaneously at high bit error rates (BER). As a result, a lot of data would be required to be retransmitted in the presence of errors. Retransmitted data may also in turn get corrupted in high BER conditions. This would result in a considerable loss of coding efficiency and increased delay. We propose the use of reversible variable length codes (RVLC) to solve this problem. RVLC not only prevents error propagation in one segment but also efficiently detects the distorted portion of the bitstream due to their capability of two-way decoding. This would allow the recovery of a large portion of data from a corrupted segment. The amount of retransmitted data can thus be drastically reduced. RVLC can be matched to various sources with different probability distributions by adjusting their suffix length, and have been found suitable for image and video coding. However, the application of RVLC to robust 3D mesh coding has not yet been studied. Our study of the suitability of RVLC for the topological data is presented in this research. Experiments have been carried to prove the efficiency of the proposed robust 3D graphic coding algorithm. To design an efficient pre-defined code table, a large set of 300 MPEG-4 selected 3D models have been used in our experiments. The use of predefined code tables would result in a significantly reduced computational complexity.
{"title":"Reversible variable length codes (RVLC) for robust coding of 3D topological mesh data","authors":"Z. Yan, Sunil Kumar, Jiankun Li, C.-C. Jay Kuo","doi":"10.1109/DCC.1999.785717","DOIUrl":"https://doi.org/10.1109/DCC.1999.785717","url":null,"abstract":"Summary form only given. In order to limit error propagation, we divide the topological data of the entire mesh into several segments. Each segment is identified by its synchronization word and header. Due to the use of the arithmetic coder, data of a whole segment would often become useless in the presence of even a single bit error. Furthermore, several adjacent segments may be corrupted simultaneously at high bit error rates (BER). As a result, a lot of data would be required to be retransmitted in the presence of errors. Retransmitted data may also in turn get corrupted in high BER conditions. This would result in a considerable loss of coding efficiency and increased delay. We propose the use of reversible variable length codes (RVLC) to solve this problem. RVLC not only prevents error propagation in one segment but also efficiently detects the distorted portion of the bitstream due to their capability of two-way decoding. This would allow the recovery of a large portion of data from a corrupted segment. The amount of retransmitted data can thus be drastically reduced. RVLC can be matched to various sources with different probability distributions by adjusting their suffix length, and have been found suitable for image and video coding. However, the application of RVLC to robust 3D mesh coding has not yet been studied. Our study of the suitability of RVLC for the topological data is presented in this research. Experiments have been carried to prove the efficiency of the proposed robust 3D graphic coding algorithm. To design an efficient pre-defined code table, a large set of 300 MPEG-4 selected 3D models have been used in our experiments. The use of predefined code tables would result in a significantly reduced computational complexity.","PeriodicalId":103598,"journal":{"name":"Proceedings DCC'99 Data Compression Conference (Cat. No. PR00096)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121843924","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}
We propose a lossy data compression scheme based on an approximate two-dimensional pattern matching (2D-PMC) extension of the Lempel-Ziv lossless scheme. We apply the scheme to image and video compression and report on our theoretical and experimental results. Theoretically, we show that the so-called fixed database model leads to suboptimal compression. Furthermore, the compression ratio of this model is as low as the generalized entropy that we define. We use this model for our video compression scheme and present experimental results. For image compression we use a growing database model. The implementation of PD-PMC is a challenging problem from the algorithmic point of view. We use a range of novel techniques and data structures such as k-d trees, generalized run length coding, adaptive arithmetic coding, and variable and adaptive maximum distortion level to achieve good compression ratios at high compression speeds. We demonstrate bit rates in the range of 0.25-0.5 bpp for high-quality images and data rates in the range of 0.15-0.4 Mbit/s for video compression.
{"title":"2D-pattern matching image and video compression","authors":"Marc Alzina, W. Szpankowski, A. Grama","doi":"10.1109/DCC.1999.755692","DOIUrl":"https://doi.org/10.1109/DCC.1999.755692","url":null,"abstract":"We propose a lossy data compression scheme based on an approximate two-dimensional pattern matching (2D-PMC) extension of the Lempel-Ziv lossless scheme. We apply the scheme to image and video compression and report on our theoretical and experimental results. Theoretically, we show that the so-called fixed database model leads to suboptimal compression. Furthermore, the compression ratio of this model is as low as the generalized entropy that we define. We use this model for our video compression scheme and present experimental results. For image compression we use a growing database model. The implementation of PD-PMC is a challenging problem from the algorithmic point of view. We use a range of novel techniques and data structures such as k-d trees, generalized run length coding, adaptive arithmetic coding, and variable and adaptive maximum distortion level to achieve good compression ratios at high compression speeds. We demonstrate bit rates in the range of 0.25-0.5 bpp for high-quality images and data rates in the range of 0.15-0.4 Mbit/s for video compression.","PeriodicalId":103598,"journal":{"name":"Proceedings DCC'99 Data Compression Conference (Cat. No. PR00096)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121938297","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}
Many applications require high-quality color images. In order to alleviate storage space and transmission time, while preserving high quality, these images are losslessly compressed. Most of the image compression algorithms treat the color image, usually in RGB format, as a set of independent gray-scale images. SICLIC is a novel inter-color coding algorithm based on a LOCO-like algorithm. It combines the simplicity of Golomb-Rice coding with the potential of context models in both intra-color and inter-color encoding. It also supports intra-color and inter-color alphabet extension, in order to reduce the redundancy of the code. SICLIC attains compression ratios superior to those obtained with most of the state-of-the-art compression algorithms and achieves compression ratios very close to those of inter-band CALIC, with much lower complexity. With arithmetic coding, SICLIC attains better compression than inter-band CALIC.
{"title":"SICLIC: a simple inter-color lossless image coder","authors":"R. Barequet, M. Feder","doi":"10.1109/DCC.1999.755700","DOIUrl":"https://doi.org/10.1109/DCC.1999.755700","url":null,"abstract":"Many applications require high-quality color images. In order to alleviate storage space and transmission time, while preserving high quality, these images are losslessly compressed. Most of the image compression algorithms treat the color image, usually in RGB format, as a set of independent gray-scale images. SICLIC is a novel inter-color coding algorithm based on a LOCO-like algorithm. It combines the simplicity of Golomb-Rice coding with the potential of context models in both intra-color and inter-color encoding. It also supports intra-color and inter-color alphabet extension, in order to reduce the redundancy of the code. SICLIC attains compression ratios superior to those obtained with most of the state-of-the-art compression algorithms and achieves compression ratios very close to those of inter-band CALIC, with much lower complexity. With arithmetic coding, SICLIC attains better compression than inter-band CALIC.","PeriodicalId":103598,"journal":{"name":"Proceedings DCC'99 Data Compression Conference (Cat. No. PR00096)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114147247","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}
Sorted Sliding Window Compression (SSWC) uses a new model (Sorted Sliding Window Model | SSWM) to encode strings e cient, which appear again while encoding a symbol sequence. The SSWM holds statistics of all strings up to certain length k in a sliding window of size n (the sliding window is de ned like in lz77). The compression program can use the SSWM to determine if the string of the next symbols are already contained in the sliding window and returns the length of match. SSWM gives directly statistics (borders of subinterval in an interval) for use in entropy encoding methods like Arithmetic Coding or Dense Coding [Gra97]. For a given number in an interval and the string length the SSWM gives back the corresponding string which is used in decompressing. After an encoding (decoding) step the model is updated with the just encoded (decoded) characters. The Model sorts all string starting points in the sliding window lexicographically. A simple way to implement the SSWM is by exhaustive search in the sliding window. An implementation with a B-tree together with special binary searches is used here. SSWC is a simple compression scheme, which uses this new model to evaluate its properties. It looks on the next characters to encode and determines the longest match with the SSWM. If the match is smaller than 2, the character is encoded. Otherwise the length and the subinterval of the string are encoded. The length values are encoded together with the single characters by using the same adaptive frequency model. Additionally some rules are used to reduce the matching length if the code length get worse. Encoding of frequencies and intervals is done with Dense Coding. SSWC is in average better than gzip [Gai93] on the Calgary corpus: 0:2 0:5 bits-per-byte better on most les and at most 0:03 bits-per-byte worse (progc and progl). This proves the quality and gives con dence in the usability of SSWM as a new building block in models for compression. SSWM has O(log k) computing complexity on all operations and needs O(n) space. SSWM can be used to implement PPM or Markov models in limited space environments because it holds all necessary informations.
{"title":"Sorted sliding window compression","authors":"U. Graf","doi":"10.1109/DCC.1999.785684","DOIUrl":"https://doi.org/10.1109/DCC.1999.785684","url":null,"abstract":"Sorted Sliding Window Compression (SSWC) uses a new model (Sorted Sliding Window Model | SSWM) to encode strings e cient, which appear again while encoding a symbol sequence. The SSWM holds statistics of all strings up to certain length k in a sliding window of size n (the sliding window is de ned like in lz77). The compression program can use the SSWM to determine if the string of the next symbols are already contained in the sliding window and returns the length of match. SSWM gives directly statistics (borders of subinterval in an interval) for use in entropy encoding methods like Arithmetic Coding or Dense Coding [Gra97]. For a given number in an interval and the string length the SSWM gives back the corresponding string which is used in decompressing. After an encoding (decoding) step the model is updated with the just encoded (decoded) characters. The Model sorts all string starting points in the sliding window lexicographically. A simple way to implement the SSWM is by exhaustive search in the sliding window. An implementation with a B-tree together with special binary searches is used here. SSWC is a simple compression scheme, which uses this new model to evaluate its properties. It looks on the next characters to encode and determines the longest match with the SSWM. If the match is smaller than 2, the character is encoded. Otherwise the length and the subinterval of the string are encoded. The length values are encoded together with the single characters by using the same adaptive frequency model. Additionally some rules are used to reduce the matching length if the code length get worse. Encoding of frequencies and intervals is done with Dense Coding. SSWC is in average better than gzip [Gai93] on the Calgary corpus: 0:2 0:5 bits-per-byte better on most les and at most 0:03 bits-per-byte worse (progc and progl). This proves the quality and gives con dence in the usability of SSWM as a new building block in models for compression. SSWM has O(log k) computing complexity on all operations and needs O(n) space. SSWM can be used to implement PPM or Markov models in limited space environments because it holds all necessary informations.","PeriodicalId":103598,"journal":{"name":"Proceedings DCC'99 Data Compression Conference (Cat. No. PR00096)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114568823","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}
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