2023 Data Compression Conference (DCC)最新文献

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Bit-Parallel (Compressed) Wavelet Tree Construction 位并行(压缩)小波树构造
2023 Data Compression Conference (DCC) Pub Date : 2023-03-01 DOI: 10.1109/DCC55655.2023.00016
P. Dinklage, J. Fischer, Florian Kurpicz, Jan-Philipp Tarnowski
{"title":"Bit-Parallel (Compressed) Wavelet Tree Construction","authors":"P. Dinklage, J. Fischer, Florian Kurpicz, Jan-Philipp Tarnowski","doi":"10.1109/DCC55655.2023.00016","DOIUrl":"https://doi.org/10.1109/DCC55655.2023.00016","url":null,"abstract":"The wavelet tree is a data structure that indexes a text over an integer alphabet for efficient rank and select queries. Using the Huffman encoding, it can be stored in zero-order entropycompressed space. We present a highly engineered open source implementation of an efficient sequential construction algorithm that makes use of bit parallelism via vector instructions. On hardware featuring ultrawide registers of up to 512 bits, it outperforms the currently fastest known practical sequential construction algorithms by a factor of up to 2.5.","PeriodicalId":209029,"journal":{"name":"2023 Data Compression Conference (DCC)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115780530","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
Contextual Pattern Matching in Less Space 更小空间的上下文模式匹配
2023 Data Compression Conference (DCC) Pub Date : 2023-03-01 DOI: 10.1109/DCC55655.2023.00024
Paniz Abedin, Oliver A. Chubet, Daniel Gibney, Sharma V. Thankachan
{"title":"Contextual Pattern Matching in Less Space","authors":"Paniz Abedin, Oliver A. Chubet, Daniel Gibney, Sharma V. Thankachan","doi":"10.1109/DCC55655.2023.00024","DOIUrl":"https://doi.org/10.1109/DCC55655.2023.00024","url":null,"abstract":"We revisit the Contextual Pattern Matching Problem, defined as follows: preprocess a text T[1, n], so that given a query consisting of a string P and a length P, the occurrences of all distinct strings XPY where |X|=|Y|=P can be reported. This problem was introduced by Navarro, who presented an O($overline{r}log(n/overline{r}))$ space data structure, where $overline{r}$ is the maximum of the number of runs in the BWT of the text $mathrm{T}[1,n]$ and its reverse. His solution reports all c contextual occurrences in $O(|P|+clog n)$ time. However, the only known bounds on $overline{r}$ are $overline{r}=O(rlog^{2}n)$ where r is the number of runs in the BWT of T, making it desirable to avoid using structures with space dependent on $overline{r}$. We demonstrate that this is possible without a significant sacrifice in query time by providing an $O(rlog(n/r))$ space solution that answers queries in $O(|P|+clog Pcdotlog(n/r))$ time.","PeriodicalId":209029,"journal":{"name":"2023 Data Compression Conference (DCC)","volume":"174 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122097854","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
On Stochastic Codebook Generation for Markov Sources 马尔可夫源的随机码本生成
2023 Data Compression Conference (DCC) Pub Date : 2023-03-01 DOI: 10.1109/DCC55655.2023.00039
Ahmed Elshafiy, K. Rose
{"title":"On Stochastic Codebook Generation for Markov Sources","authors":"Ahmed Elshafiy, K. Rose","doi":"10.1109/DCC55655.2023.00039","DOIUrl":"https://doi.org/10.1109/DCC55655.2023.00039","url":null,"abstract":"This paper proposes an effective universal (on-the-Hy’’ mechanism for stochastic codebook generation in lossy coding of Markov sources. Earlier work has shown that the ratedistortion bound can be asymptotically achieved by a “natural type selection” (NTS) mechanism that iteratively considers asymptotically long source strings (from an unknown distribution P) and regenerates the codebook from a distribution obtained within a maximum likelihood distribution estimation framework, based on observation of a set of K codewords that “d-match’’ (i.e., satisfy the distortion constraint for) a respective set of K independently generated source words. This result was later generalized, in a straightforward manner, to account for source memory, by considering the source as a vector source, i.e., a sequence of super-symbols from a corresponding super-alphabet. While ensuring asymptotic optimality, this extension suffered from a significant practical flaw: it requires asymptotically long vectors or super-symbols, hence exponentially large super-alphabet, in order to approach the rate-distortion bound, even for finite memory sources, e.g., Markov sources. Such exponentially large super-alphabet implies that even a single NTS iteration is intractable, thus compromising the promise of NTS to approach the rate-distortion function, in practice, for sources with memory. This work describes a considerably more efficient and tractable mechanism to achieve asymptotically optimal performance given a prescribed memory constraint, within a practical framework tailored to Markov sources. Specifically, the algorithm finds, asymptotically, the optimal codebook reproduction distribution, within a constrained set of distributions satisfying a prescribed Markovian property, e.g., of the same order as the source, which achieves the minimum per letter coding rate while maintaining a specified distortion level.","PeriodicalId":209029,"journal":{"name":"2023 Data Compression Conference (DCC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132748719","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 debanding algorithm for AV2 AV2的去带算法
2023 Data Compression Conference (DCC) Pub Date : 2023-03-01 DOI: 10.1109/dcc55655.2023.00034
J. Solé, Mariana Afonso
{"title":"A debanding algorithm for AV2","authors":"J. Solé, Mariana Afonso","doi":"10.1109/dcc55655.2023.00034","DOIUrl":"https://doi.org/10.1109/dcc55655.2023.00034","url":null,"abstract":"Banding is a visually unpleasing artifact appearing in flat areas of encoded content that no video standard has fully addressed. We propose a normative debanding filter to tackle banding artifacts and have tested it as an inloop and post-loop filter in AVM. Debanding is achieved by introducing dithering on a frame level to the luma component. The proposed filter shows CAMBI gains for content with banding while not affecting other content. Although the added dithering has a minor negative impact on some objective metrics, subjective improvements in banding-prone content are (informally) observed. On the test set, encoding time increases on average by ~0.5%, while decoding time increases by around 0.5% for in-loop and 1.5% for post-loop.","PeriodicalId":209029,"journal":{"name":"2023 Data Compression Conference (DCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133425322","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
Invert-and-project (IVP): A Lossless Compression Method of Multi-scale JPEG Images via DCT Coefficients Prediction 反演投影:一种基于DCT系数预测的多尺度JPEG图像无损压缩方法
2023 Data Compression Conference (DCC) Pub Date : 2023-03-01 DOI: 10.1109/DCC55655.2023.00089
Haohan Li, Zhao Sun, Jie Sun
{"title":"Invert-and-project (IVP): A Lossless Compression Method of Multi-scale JPEG Images via DCT Coefficients Prediction","authors":"Haohan Li, Zhao Sun, Jie Sun","doi":"10.1109/DCC55655.2023.00089","DOIUrl":"https://doi.org/10.1109/DCC55655.2023.00089","url":null,"abstract":"JPEG is a widely used format for images. Most JPEG variants are based upon a block-based DCT transformation followed by quantization and entropy coding. Redundancy at row/column level is explored in [1]. Brunsli [2] and Lepton [3], lossless JPEG repacking libraries, explore redundancy at block level.","PeriodicalId":209029,"journal":{"name":"2023 Data Compression Conference (DCC)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124969615","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 Parallel ANS Coder with Reduced Decoding Error Diffusion 减少译码错误扩散的并行ANS编码器
2023 Data Compression Conference (DCC) Pub Date : 2023-03-01 DOI: 10.1109/DCC55655.2023.00021
Na Wang, Zhengrui Li, Sian-Jheng Lin
{"title":"A Parallel ANS Coder with Reduced Decoding Error Diffusion","authors":"Na Wang, Zhengrui Li, Sian-Jheng Lin","doi":"10.1109/DCC55655.2023.00021","DOIUrl":"https://doi.org/10.1109/DCC55655.2023.00021","url":null,"abstract":"The Asymmetrical Numeral Systems (ANS) coding has received significant attention in well-integrated compression systems. One particularly insightful technique that has emerged is the interleaved ANS coder (IAC), which substantially enhances the throughput by using multiple encoders and decoders. However, IAC has a limitation that even a single bit error in the compressed bitstream may diffuse across multiple decoders, resulting in many symbols to be incorrectly decoded. In this paper, we propose a parallel method to mitigate the diffusion for a class of error patterns, by limiting the errors to affect only a single decoder. The simulation results show that compared with IAC, our proposal can reduce the average number of incorrectly decoded symbols by about 50% while maintaining comparable encoding and decoding throughput.","PeriodicalId":209029,"journal":{"name":"2023 Data Compression Conference (DCC)","volume":"349 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129135552","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
JARVIS2: a data compressor for large genome sequences JARVIS2:用于大基因组序列的数据压缩器
2023 Data Compression Conference (DCC) Pub Date : 2023-03-01 DOI: 10.1109/DCC55655.2023.00037
Diogo Pratas, A. Pinho
{"title":"JARVIS2: a data compressor for large genome sequences","authors":"Diogo Pratas, A. Pinho","doi":"10.1109/DCC55655.2023.00037","DOIUrl":"https://doi.org/10.1109/DCC55655.2023.00037","url":null,"abstract":"Reducing data storage and its associated costs is one of the major bottlenecks in large-scale genomic projects. In this paper, we present a new method for efficient reference-free data compression of genomic sequences, using a mixture of multiple finite-context models (FCMs) and weighted local stochastic repeat models (WLSRMs). In the WLSRMs, we developed a new cache-hash memory model for increasing the compression ratio, while decreasing the RAM. The mixture is provided by a new architecture, that includes a neural network, followed by arithmetic encoding. The method is implemented using the C language as the JARVIS2 tool. Additionally, we provide a C/Bash implementation for using JARVIS2 in FASTA data. The results show an improvement in the compression of two extensive datasets, while using lower computational resources relative to the second best compression ratio tool. JARVIS2 is freely available at https://github.com/cobilab/jarvis2.","PeriodicalId":209029,"journal":{"name":"2023 Data Compression Conference (DCC)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129654704","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
High performance predictor blending lossless image coder 高性能预测混合无损图像编码器
2023 Data Compression Conference (DCC) Pub Date : 2023-03-01 DOI: 10.1109/DCC55655.2023.00066
G. Ulacha, R. Stasinski
{"title":"High performance predictor blending lossless image coder","authors":"G. Ulacha, R. Stasinski","doi":"10.1109/DCC55655.2023.00066","DOIUrl":"https://doi.org/10.1109/DCC55655.2023.00066","url":null,"abstract":"In the paper a highly efficient algorithm for lossless image coding is described. The algorithm is a predictor blending one, a sample estimate is computed as a weighted sum of estimates given by subpredictors, here 27 ones, hence the name Blend-27. The subpredictors varies from 15 based on 1-3 neighbouring pixels, to much more powerful even if working alone. The predictor blending formula is adaptive, and favors locally the best sub-predictors in a neighborhood. The algorithm is a cascade one: some sub-predictors are followed by two consecutive NLMS filters. Additionaly, in the fourth cascade stage sub-predictor bias cancellation can be done. Update formulas on NLMS coefficients and description of twelve bias canceling methods can be found in [1]. Entropy coder is a highly sophisticated arithmetic one, it is described in [1].","PeriodicalId":209029,"journal":{"name":"2023 Data Compression Conference (DCC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128921347","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
Constructing the CDAWG CFG using LCP-Intervals 使用lcp - interval构造CDAWG CFG
2023 Data Compression Conference (DCC) Pub Date : 2023-03-01 DOI: 10.1109/DCC55655.2023.00026
Alan M. Cleary, Jordan Dood
{"title":"Constructing the CDAWG CFG using LCP-Intervals","authors":"Alan M. Cleary, Jordan Dood","doi":"10.1109/DCC55655.2023.00026","DOIUrl":"https://doi.org/10.1109/DCC55655.2023.00026","url":null,"abstract":"It is known that a context-free grammar (CFG) that produces a single string can be derived from the compact directed acyclic word graph (CDAWG) for the same string. In this work, we show that the CFG derived from a CDAWG is deeply connected to the maximal repeat content of the string it produces and thus has O(m) rules, where m is the number of maximal repeats in the string. We then provide a generic algorithm based on this insight for constructing the CFG from the LCP-intervals of a string in O(n) time, where n is the length of the string. This includes a novel data-structure to support stabbing queries on LCPintervals in O(1+k) time after O(n) preprocessing time, where k is the number of intervals stabbed. These results connect the CFG to properties of the string it produces and relates it to other string data-structures, allowing it to be studied independently of the CDAWG and providing opportunity for innovation of grammar-based compression algorithms.","PeriodicalId":209029,"journal":{"name":"2023 Data Compression Conference (DCC)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115592939","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
Batch Denoising via Blahut-Arimoto 通过Blahut-Arimoto进行批处理去噪
2023 Data Compression Conference (DCC) Pub Date : 2023-03-01 DOI: 10.1109/DCC55655.2023.00043
Qing Li, Cyril Guyot
{"title":"Batch Denoising via Blahut-Arimoto","authors":"Qing Li, Cyril Guyot","doi":"10.1109/DCC55655.2023.00043","DOIUrl":"https://doi.org/10.1109/DCC55655.2023.00043","url":null,"abstract":"In this work, we propose a method for solving batch denoising using the Blahut-Arimoto algorithm (BA). Theoretical results show that our denoising estimation is highly likely to be close to the best result.","PeriodicalId":209029,"journal":{"name":"2023 Data Compression Conference (DCC)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131025155","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
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