2013 Data Compression Conference最新文献_第3页

Ultra Fast H.264/AVC to HEVC Transcoder 超快速H.264/AVC到HEVC转码器

2013 Data Compression Conference Pub Date : 2013-03-20 DOI: 10.1109/DCC.2013.32

Tong Shen, Yao Lu, Ziyu Wen, Linxi Zou, Yucong Chen, Jiangtao Wen

引用次数: 39

STOL: Spatio-Temporal Online Dictionary Learning for Low Bit-Rate Video Coding 低比特率视频编码的时空在线词典学习

2013 Data Compression Conference Pub Date : 2013-03-20 DOI: 10.1109/DCC.2013.101

Xin Tang, H. Xiong

{"title":"STOL: Spatio-Temporal Online Dictionary Learning for Low Bit-Rate Video Coding","authors":"Xin Tang, H. Xiong","doi":"10.1109/DCC.2013.101","DOIUrl":"https://doi.org/10.1109/DCC.2013.101","url":null,"abstract":"To speed up the convergence rate of learning dictionary in low bit-rate video coding, this paper proposes a spatio-temporal online dictionary learning (STOL) algorithm to improve the original adaptive regularized dictionary learning with K-SVD which involves a high computational complexity and interfere with the coding efficiency. Considering the intrinsic dimensionality of the primitives in training each series of 2-D sub dictionaries is low, the 3-D low-frequency and high-frequency dictionary pair would be formed by the online dictionary learning to update the atoms for optimal sparse representation and convergence. Instead of classical first-order stochastic gradient descent on the constraint set, e.g. K-SVD, the online algorithm would exploit the structure of sparse coding in the design of an optimization procedure in terms of stochastic approximations. It depends on low memory consumption and lower computational cost without the need of explicit learning rate tuning. Through drawing a cubic from i.i.d. samples of a distribution in each inner loop and alternating classical sparse coding steps for computing the decomposition coefficient of the cubic over previous dictionary, the dictionary update problem is converted to solve the expected cost instead of the empirical cost. For dynamic training data over time, online dictionary learning behaves faster than second-order iteration batch alternatives, e.g. K-SVD. Through experiments, the super-resolution reconstruction based on STOL obviously reduces the computational complexity to 40% to 50% of the K-SVD learning-based schemes with a guaranteed accuracy.","PeriodicalId":388717,"journal":{"name":"2013 Data Compression Conference","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132579539","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

A Compression Algorithm for Fluctuant Data in Smart Grid Database Systems 智能电网数据库系统中波动数据的压缩算法

2013 Data Compression Conference Pub Date : 2013-03-20 DOI: 10.1109/DCC.2013.67

Chi-Cheng Chuang, Y. Chiu, Zhi-Hung Chen, Hao-Ping Kang, Che-Rung Lee

{"title":"A Compression Algorithm for Fluctuant Data in Smart Grid Database Systems","authors":"Chi-Cheng Chuang, Y. Chiu, Zhi-Hung Chen, Hao-Ping Kang, Che-Rung Lee","doi":"10.1109/DCC.2013.67","DOIUrl":"https://doi.org/10.1109/DCC.2013.67","url":null,"abstract":"In this paper, we present a lossless compression algorithm for fluctuant data, which can be integrated into database system and allows regular database insertion and queries. The algorithm is based on the observation that fluctuant data, although varied violently during small time intervals, have similar patterns over time. The algorithm first partitioned consecutive k records into segments. Those segments are normalized and treated as vectors in k-dimensional space. Classification algorithms are then applied to find representative vectors for those normalized vectors. The classification criterion is that any segments after normalization can find at least one representative vector such that their distance is less than a given threshold. Those representative vectors, called codes, are stored in a codebook. The codebook can be generated offline from a small training dataset, and used repeatedly. The online compression algorithm searches the nearest code for an input segment, and stores only the ID of the code and their difference. Since the difference is small, it can be compressed by Rice coding or Golomb coding.lossless compression algorithm.","PeriodicalId":388717,"journal":{"name":"2013 Data Compression Conference","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134461135","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: 4

Natural Language Compression Optimized for Large Set of Files 为大型文件集优化的自然语言压缩

2013 Data Compression Conference Pub Date : 2013-03-20 DOI: 10.1109/DCC.2013.93

P. Procházka, J. Holub

{"title":"Natural Language Compression Optimized for Large Set of Files","authors":"P. Procházka, J. Holub","doi":"10.1109/DCC.2013.93","DOIUrl":"https://doi.org/10.1109/DCC.2013.93","url":null,"abstract":"Summary form only given. The web search engines store the web pages in the raw text form to build so called snippets (short text surrounding the searched pattern) or to perform so called positional ranking functions. We address the problem of the compression of a large collection of text files distributed in cluster of computers, where the single files need to be randomly accessed in very short time. The compression algorithm Set-of-Files Semi-Adaptive Two Byte Dense Code (SF-STBDC) is based on the word-based approach and the idea of combination of two statistical models: the global model (common for all the files of the set) and the local model. The latter is built as the set of changes which transform the global model to the proper model of the single compressed file. Except very good compression ratio the compression method allows fast searching on the compressed text, which is an attractive property especially for search engines property especially for search engines. Exactly the same problem (compression of a set of files using byte codes) was first stated in. Our algorithm SF-STBDC overcomes the algorithm based on (s,c) - Dense Code in compression ratio and at the same time it keeps a very good searching and decompression speed. The key idea to achieve this result is a usage of Semi-Adaptive Two Byte Dense Code which provides more effective coding of small portions ofof the text and still allows exact setting of the number of stoppers and continuers.","PeriodicalId":388717,"journal":{"name":"2013 Data Compression Conference","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133287552","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

Analog Joint Source Channel Coding over Non-Linear Channels 非线性信道上的模拟联合源信道编码

2013 Data Compression Conference Pub Date : 2013-03-20 DOI: 10.1109/DCC.2013.75

Mohamed Hassanin, J. Garcia-Frías

引用次数: 2

Near in Place Linear Time Minimum Redundancy Coding 近就地线性时间最小冗余编码

2013 Data Compression Conference Pub Date : 2013-03-20 DOI: 10.1109/DCC.2013.49

Juha Kärkkäinen, German Tischler

引用次数: 4

Variable-to-Fixed-Length Encoding for Large Texts Using Re-Pair Algorithm with Shared Dictionaries 基于共享字典的重对算法的大文本变到定长编码

2013 Data Compression Conference Pub Date : 2013-03-20 DOI: 10.1109/DCC.2013.97

Kei Sekine, Hirohito Sasakawa, S. Yoshida, T. Kida

引用次数: 2

Simplified HEVC FME Interpolation Unit Targeting a Low Cost and High Throughput Hardware Design 针对低成本和高吞吐量硬件设计的简化HEVC FME插补单元

2013 Data Compression Conference Pub Date : 2013-03-20 DOI: 10.1109/DCC.2013.55

Vladimir Afonso, Henrique Maich, L. Agostini, Denis Franco

{"title":"Simplified HEVC FME Interpolation Unit Targeting a Low Cost and High Throughput Hardware Design","authors":"Vladimir Afonso, Henrique Maich, L. Agostini, Denis Franco","doi":"10.1109/DCC.2013.55","DOIUrl":"https://doi.org/10.1109/DCC.2013.55","url":null,"abstract":"Summary form only given. The new demands for high resolution digital video applications are pushing the development of new techniques in the video coding area. This paper presents a simplified version of the original Fractional Motion Estimation (FME) algorithm defined by the HEVC emerging video coding standard targeting a low cost and high throughput hardware design. Based on evaluations using the HEVC Model (HM), the HEVC reference software, a simplification strategy was defined to be used in the hardware design, drastically reducing the HEVC complexity, but with some losses in terms of compression rates and quality. The used strategy considered the use of only the most used PU size in the Motion Estimation process, avoiding the evaluation of the 24 PU sizes defined in the HEVC and avoiding also the RDO decision process. This expressively reduces the ME complexity and causes a bit-rate loss lower than 13.18% and a quality loss lower than 0.45dB. Even with the proposed simplification, the proposed solution is fully compliant with the current version of the HEVC standard. The FME interpolation was also simplified targeting the hardware design through some algebraic manipulations, converting multiplications in shift-adds and sharing sub-expressions. The simplified FME interpolator was designed in hardware and the results showed a low use of hardware resources and a processing rate high enough to process QFHD videos (3840x2160 pixels) in real time.","PeriodicalId":388717,"journal":{"name":"2013 Data Compression Conference","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127397436","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: 5

A High Throughput Multi Symbol CABAC Framework for Hybrid Video Codecs 用于混合视频编解码器的高吞吐量多符号CABAC框架

2013 Data Compression Conference Pub Date : 2013-03-20 DOI: 10.1109/DCC.2013.94

K. Rapaka, E. Yang

引用次数: 1

Lossless Compression of Rotated Maskless Lithography Images 旋转无掩模光刻图像的无损压缩

2013 Data Compression Conference Pub Date : 2013-03-20 DOI: 10.1109/DCC.2013.80

S. T. Klein, Dana Shapira, Gal Shelef

引用次数: 1