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Novel region-based image compression method based on spiking cortical model

Journal of Systems Engineering and Electronics 2015年第1期26卷 161-171页

作者： Rongchang Zhao Yide Ma School of Information Science and Engineering Central South University School of Information Science & Engineering Lanzhou University

To get the high compression ratio as well as the high-quality reconstructed image, an effective image compression scheme named irregular segmentation region coding based on spiking cortical model（ISRCS） is presented. This scheme is region-based and mainly focuses on two issues. Firstly, an appropriate segmentation algorithm is developed to partition an image into some irregular regions and tidy contours, where the crucial regions corresponding to objects are retained and a lot of tiny parts are eliminated. The irregular regions and contours are coded using different methods respectively in the next step. The other issue is the coding method of contours where an efficient and novel chain code is employed. This scheme tries to find a compromise between the quality of reconstructed images and the compression ratio. Some principles and experiments are conducted and the results show its higher performance compared with other compression technologies, in terms of higher quality of reconstructed images, higher compression ratio and less time consuming.

关键词： data compaction and compression image processing and computer vision region-based image coding neural network

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A Binary Line Buffer Circuit Featuring Lossy data compression at Fixed Maximum data Rate

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS 2020年第1期67卷 121-134页

作者： Napoli, Ettore De Caro, Davide Petra, Nicola Strollo, Antonio Giuseppe Maria Univ Napoli Federico II Dept Elect & Informat Technol Engn I-80125 Naples Italy

Video processing requires an increasing amount of buffered data. The paper proposes a multi-line buffer circuit that stores compressed data thus saving logic and power. The lossy compression algorithm provides the output stream with a fixed, decided by the user, delay from the input stream. Further, the amount of memory of the compressed buffer can be designed to trade off the correctness of the output with the logic resources footprint. The circuit is tested in a computer vision processing chain as a binary line buffer for the stream of foreground pixels. The paper also proposes a multi-line buffer circuit that integrates a morphological operation. The latter, when compared against the state of the art and against the proposed multi-line lossy buffer, allows larger saving of logic resources (up to 75) and power (up to 85), with reduced penalty on video quality.

关键词： Streaming media Memory management Buffer storage Image coding Transform coding Shift registers Low power design VLSI sequential circuits shift register data compaction and compression computer vision video compression

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Prefix Coding Scheme Supporting Direct Access Without Auxiliary Space

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IEEE TRANSACTIONS ON KNOWLEDGE AND data ENGINEERING 2023年第12期35卷 12917-12931页

作者： Wang, Na Yan, Wei Jiang, Hao Lin, Sian-Jheng Han, Yunghsiang S. Univ Shanghai Sci & Technol Sch Optoelect Informat & Comp Engn Shanghai 200093 Peoples R China Huawei Technol Co Ltd Theory Lab Hefei 230000 Peoples R China Huawei Technol Co Ltd Theory Lab Hong Kong Peoples R China Alibaba Grp Hangzhou 311121 Peoples R China Univ Elect Sci & Technol China Shenzhen Inst Adv Study Shenzhen 518110 Peoples R China

Entropy coding is a widely used technique for lossless data compression. The entropy coding schemes supporting the direct access capability on the encoded stream have been investigated in recent years. However, all prior schemes require auxiliary space to support the direct access ability. This paper proposes a rearranging method for prefix codes to support a certain level of direct access to the encoded stream without requiring additional data space. Then, an efficient decoding algorithm is proposed based on lookup tables. The simulation results show that when the encoded stream does not allow additional space, the number of bits per access read of the proposed method is above two orders of magnitude less than the conventional method. In contrast, the alternative solution consumes at least one more bit per symbol on average than the proposed method to support direct access. This indicates that the proposed scheme can achieve a good trade-off between space usage and access performance. In addition, if a small amount of additional storage space is allowed (it is approximately 0.057% in the simulation), the number of bits per access read in our proposal can be significantly reduced by 90%.

关键词： And additional data space data compaction and compression direct access entropy coding prefix codes

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DELTA plus plus : Reducing the Size of Android Application Updates

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IEEE INTERNET COMPUTING 2014年第2期18卷 50-57页

作者： Samteladze, Nikolai Christensen, Ken Univ S Florida Tampa FL 33620 USA Univ S Florida Dept Comp Sci & Engn Tampa FL 33620 USA

This method of creating and deploying update patches improves on Google Smart Application Update by first unpacking the Android Application Package and then compressing its elements individually. The smartphone user can then download a smaller patch. Experiments show that performance yields 49 percent more reduction relative to Google's solution, increasing the savings in cellular network bandwidth use and resulting in lighter application server loads. This reduction in Android application-update traffic could translate to a 1.7 percent decrease in annual US cellular traffic. Similar methods applied to iPhone application updates could yield even greater savings.

关键词： Google Androids Humanoid Robots Smart Phones Encoding Internet Servers Telecommunication Traffic Android Mobile Applications data compaction and compression Delta Encoding

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A SISO Register Circuit Tailored for Input data with Low Transition Probability

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IEEE TRANSACTIONS ON COMPUTERS 2017年第1期66卷 45-51页

作者： Napoli, Ettore Castellano, Gerardo De Caro, Davide Esposito, Darjn Petra, Nicola Strollo, Antonio G. M. Univ Napoli Federico II Dept Elect & Informat Technol Enginnering Via Claudio21 I-80125 Naples Italy

The paper proposes a SISO register circuit, functionally equivalent to a Shift Register, that is the optimal design choice when the input data have a reduced transition probability. The proposed circuit obtains improv... 详细信息

关键词： data compaction and compression low power design VLSI sequential circuits shift register

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Progressive Tree-Based compression of Large-Scale Particle data

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IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2024年第7期30卷 4321-4338页

作者： Hoang, Duong Bhatia, Harsh Lindstrom, Peter Pascucci, Valerio Univ Utah Sci Comp & Imaging Inst Salt Lake City UT 84112 USA Lawrence Livermore Natl Lab Ctr Appl Sci Comp Livermore CA 94550 USA

Scientific simulations and observations using particles have been creating large datasets that require effective and efficient data reduction to store, transfer, and analyze. However, current approaches either compress only small data well while being inefficient for large data, or handle large data but with insufficient compression. Toward effective and scalable compression/decompression of particle positions, we introduce new kinds of particle hierarchies and corresponding traversal orders that quickly reduce reconstruction error while being fast and low in memory footprint. Our solution to compression of large-scale particle data is a flexible block-based hierarchy that supports progressive, random-access, and error-driven decoding, where error estimation heuristics can be supplied by the user. For low-level node encoding, we introduce new schemes that effectively compress both uniform and densely structured particle distributions. Our proposed methods thus target all three phases of a tree-based particle compression pipeline, namely tree construction, tree traversal, and node encoding. The improved efficacy and flexibility of these methods over existing compressors are demonstrated through extensive experimentation, using a wide range of scientific particle datasets.

关键词： Encoding Decoding Image reconstruction data models Computational modeling Compressors Task analysis Coarse approximation compression (coding) data compaction and compression hierarchical multiresolution particle datasets progressive decompression tree traversal visualization

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Pattern matching in LZW compressed files

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IEEE TRANSACTIONS ON COMPUTERS 2005年第8期54卷 929-938页

作者： Tao, T Mukherjee, A Univ Cent Florida Sch Comp Sci Orlando FL 32826 USA

Compressed pattern matching is an emerging research area that addresses the following problem: Given a text file in compressed format and a pattern, report the occurrence(s) of the pattern in the file with minimal ( or no) decompression. In this paper, we report our work on compressed pattern matching in LZW compressed files. The work includes an extension of Amir et al.'s well-known "almost-optimal" algorithm. The original Amir et al.'s algorithm has been improved to search not only the first occurrence of the pattern but also all other occurrences. A faster implementation for so-called "simple patterns" is also proposed. The work also includes a novel multiple-pattern matching algorithm using the Aho-Corasick algorithm. The algorithm takes O(mt+n+r) time with O(mt) extra space, where n is the size of the compressed file, m is the total length of all patterns, t is the size of the LZW trie, and r is the number of occurrences of the patterns. Extensive experiments have been conducted to test the performance of our algorithms and to compare with other well-known compressed pattern matching algorithms, particularly the BWT-based algorithms and another similar multiple-pattern matching algorithm by Kida et al. that also uses the Aho-Corasick algorithm on the LZW compressed data. The results showed that our multiple-pattern matching algorithm is competitive among the best compressed pattern-matching algorithms and is practically the fastest among all approaches when the number of patterns is not very large. Therefore, our algorithm is preferable for general string matching applications. The proposed algorithm is efficient for large files and it is particularly efficient when being applied on archive search if the archives are compressed with a common LZW trie. LZW is one of the most efficient and popular compression algorithms used extensively and our method requires no modification on the compression algorithm. The work reported in this paper, therefore, has great econ

关键词： data compaction and compression information search and retrieval pattern matching

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引用

IEEE TRANSACTIONS ON KNOWLEDGE AND data ENGINEERING 2008年第4期20卷 562-575页

作者： Gueguen, Lionel Datcu, Mihai GET Telecom Paris Dept TSI F-75013 Paris France IMF DLR German Aerosp Ctr D-82234 Wessling Germany

This paper addresses the problem of building an index of compressed object databases. We introduce an informational similarity measure based on the coding length of two part Codes. Then, we present a methodology for compressing the database by taking into account interobject redundancies and by using the informational similarity measure. The method produces an index included in the code of the data volume. This index is built Such that it contains the minimal sufficient information to discriminate the data-volume objects. Then, we present an optimal two-part coder for compressing spatio-temporal events contained in Satellite Image Time Series (SITS). The two-part coder allows us to measure similarity and then to derive an optimal index of SITS spatio-temporal events, The resulting index is representative of the SITS information content and enables queries based on information content.

关键词： database design modeling and management context analysis and indexing data compaction and compression complexity measures and classes,model theory time series analysis

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Binary RDF representation for publication and exchange (HDT)

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JOURNAL OF WEB SEMANTICS 2013年 19卷 22-41页

作者： Fernandez, Javier D. Martinez-Prieto, Miguel A. Gutierrez, Claudio Polleres, Axel Arias, Mario Univ Valladolid Dept Comp Sci ETS Ingn Informat DataWeb Res E-47011 Valladolid Spain Univ Chile Dept Comp Sci Santiago 8370459 Chile Natl Univ Ireland Digital Enterprise Res Inst Galway Ireland Siemens AG Osterreich A-1210 Vienna Austria

The current Web of data is producing increasingly large RDF datasets. Massive publication efforts of RDF data driven by initiatives like the Linked Open data movement, and the need to exchange large datasets has unveiled the drawbacks of traditional RDF representations, inspired and designed by a document-centric and human-readable Web. Among the main problems are high levels of verbosity/redundancy and weak machine-processable capabilities in the description of these datasets. This scenario calls for efficient formats for publication and exchange. This article presents a binary RDF representation addressing these issues. Based on a set of metrics that characterizes the skewed structure of real-world RDF data, we develop a proposal of an RDF representation that modularly partitions and efficiently represents three components of RDF datasets: Header information, a Dictionary, and the actual Triples structure (thus called HDT). Our experimental evaluation shows that datasets in HDT format can be compacted by more than fifteen times as compared to current naive representations, improving both parsing and processing while keeping a consistent publication scheme. Specific compression techniques over HDT further improve these compression rates and prove to outperform existing compression solutions for efficient RDF exchange. (c) 2013 Elsevier B.V. All rights reserved.

关键词： RDF Binary formats data compaction and compression RDF metrics

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FadingBF: A Bloom Filter With Consistent Guarantees for Online Applications

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IEEE TRANSACTIONS ON COMPUTERS 2022年第1期71卷 40-52页

作者： Vairam, Prasanna Karthik Kumar, Pratyush Rebeiro, Chester Kamakoti, V Indian Inst Technol Madras Dept Comp Sci & Engn Chennai 600036 Tamil Nadu India

Bloom filter (BF), when used by an online application, experiences monotonically increasing false-positive errors. The decay of stale elements can control false-positives. Existing mechanisms for decay require unreasonable storage and computation. Inexpensive methods reset the BF periodically, resulting in inconsistent guarantees and performance issues in the underlying computing system. In this article, we propose Fading Bloom filter (FadingBF), which can provide inexpensive yet safe decay of elements. FadingBF neither requires additional storage nor computation to achieve this but instead exploits the underlying storage medium's intrinsic properties, i.e., DRAM capacitor characteristics. We realize FadingBF by implementing the BF on a DRAM memory module with its periodic refresh disabled. Consequently, the capacitors holding the data elements that are not accessed frequently will predictably lose charge and naturally decay. The retention time of capacitors guarantees against premature deletion. However, some capacitors may store information longer than required due to the FadingBF's software and hardware variables. Using an analytical model of the FadingBF, we show that carefully tuning its parameters can minimize such cases. For a surveillance application, we demonstrate that FadingBF achieves better guarantees through graceful decay, consumes 57 percent lesser energy, and has a system load that is lesser than the standard BF.

关键词： Random access memory Capacitors Standards Memory management Surveillance Fading channels Analytical models Online information services dynamic storage management data storage representations data compaction and compression bloom filters false negatives DRAM capacitors surveillance systems Internet of Things

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