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检索条件"主题词=Compression algorithms"

共 2068 条记录，以下是281-290 订阅

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Concurrent Encryption and Lossless compression using Inversion Ranks

Concurrent Encryption and Lossless Compression using Inversi...

引用

Data compression Conference (DCC)

作者： Koc, Basar Arnavut, Ziya Kocak, Huseyin Stetson Univ Dept Comp Sci Deland FL 32723 USA SUNY Coll Fredonia Dept Comp Sci Fredonia NY 14063 USA Univ Miami Dept Comp Sci Coral Gables FL 33124 USA

ISBN: (纸本)9781665478939

For secure and efficient transmission or storage, data files are commonly compressed and encrypted. In this work, we introduce a cost-effective encryption method of files as a built-in component of a lossless compression algorithm, thus avoiding the added cost of employing two separate processes. We have shown in earlier studies that preprocessing data with Burrows-Wheeler Transformation followed by Inversion Ranking transformation in advance of the utilization of an entropy coder resulted in an extremely effective general-purpose lossless compression technique [1], [2]. During the compression process, we encrypt the frequency vector of the Inversion Ranking transformation and transmit it along with the compressed data. Since the frequency vector is required for decompression, no further encryption is necessary to secure the compressed file, see Figure 1.

关键词： Costs Data compression Entropy Encryption compression algorithms

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An error-resilient blocksorting compression algorithm

An error-resilient blocksorting compression algorithm

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Data compression Conference 2003 (DCC2003)

作者： Butterman, L Memon, N Brown Univ Dept Comp Sci Providence RI 02912 USA

ISBN: (纸本)0769518966

Summary form only given. The error susceptibility in the compressed bit stream is considered as a key limitation of adaptive lossless compression systems. The inherent design of these systems often requires that they discard all data subsequent to the error. This is especially problematic in the Burrows-Wheeler blocksorting transform (BWT), with 1MB suffix-sorted blocks. Error-correcting codes, such as Reed-Solomon codes, can be used but their design allows for a maximum pre-fixed error rate. If the channel errors exceed the maximum pre-fixed error rate, the whole block is lost. An error resilient version of the BWT was presented that has error-free output in low channel noise. It gracefully degrades output quality, as errors increase by scattering output errors, and avoids significant error propagation typical with adaptive lossless compression systems. These techniques give interesting new insights on the increasingly popular compression algorithm. © 2003 IEEE.

关键词： Adaptive systems Character generation compression algorithms Computer science Decoding Degradation Error analysis Error correction codes Histograms Reed-Solomon codes

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An Accelerometer Lossless compression Algorithm and Energy Analysis for IoT Devices

An Accelerometer Lossless Compression Algorithm and Energy A...

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IEEE Wireless Communications and Networking Conference (WCNC)

作者： Pope, James Vafeas, Antonis Elsts, Atis Oikonomou, George Piechocki, Robert Craddock, Ian Univ Bristol Dept Elect & Elect Engn Bristol Avon England

ISBN: (纸本)9781538611548

The Internet of Things promises to enable numerous future applications spanning many domains, including health care, and is comprised of devices that are constrained in terms of computational and energy resources. A specific health care application is to ascertain patients' activity of daily living while at home using accelerometer data from non-invasive wearables. It is often necessary to store this data on the device to be retrieved later for analysis. However, the devices typically store far more data than can be transmitted with commonly used low power radios. To mitigate the problem, this paper proposes an energy efficient, lossless compression algorithm that uses an offline frequency distribution to create a symbol-code lookup table. Using an extensive set of data from a previous study, an analysis of the entropy of activities of daily living accelerometer data is presented. The compression algorithm is compared against this estimated entropy. Energy being critical for IoT devices, the trade-off between energy cost for compression versus energy saved during transmission is also analysed.

关键词： Entropy Accelerometers Conferences Medical services compression algorithms Biomedical monitoring Dictionaries

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MR-RePair: Grammar compression based on Maximal Repeats

MR-RePair: Grammar Compression based on Maximal Repeats

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Data compression Conference (DCC)

作者： Furuya, Isamu Takagi, Takuya Nakashima, Yuto Inenaga, Shunsuke Bannai, Hideo Kida, Takuya Hokkaido Univ Grad Sch IST Sapporo Hokkaido Japan Kyushu Univ Dept Informat Fukuoka Japan

ISBN: (纸本)9781728106571

We analyze the grammar generation algorithm of the RePair compression algorithm and show the relation between a grammar generated by RePair and maximal repeats. We reveal that RePair replaces step by step the most frequent pairs within the corresponding most frequent maximal repeats. Then, we design a novel variant of RePair, called MR-RePair, which substitutes the most frequent maximal repeats at once instead of substituting the most frequent pairs consecutively. We implemented MR-RePair and compared the size of the grammar generated by MR-RePair to that by RePair on several text corpora. Our experiments show that MR-RePair generates more compact grammars than RePair does, especially for highly repetitive texts.

关键词： Maintenance engineering Grammar Production Data compression compression algorithms Informatics Upper bound

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A Grammar compression Algorithm based on Induced Suffix Sorting

A Grammar Compression Algorithm based on Induced Suffix Sort...

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Data compression Conference (DCC)

作者： Nogueira Nunes, Daniel Saad Louza, Felipe A. Gog, Simon Ayala-Rincon, Mauricio Navarro, Gonzalo Fed Inst Educ Sci & Technol Brasilia Brasilia DF Brazil Univ Brasilia Dept Comp Sci Brasilia DF Brazil Univ Sao Paulo Dept Comp & Math Sao Paulo Brazil Karlsruhe Inst Technol Inst Theoret Informat Karlsruhe Germany Univ Chile Dept Comp Sci Ctr Biotechnol & Bioengn Santiago Chile

ISBN: (纸本)9781538648834

We introduce GCIS, a grammar compression algorithm based on the induced suffix sorting algorithm SAIS, presented by Nong et al. in 2009. Our solution builds on the factorization performed by SAIS during suffix sorting. We construct a context-free grammar on the input string which can be further reduced into a shorter string by substituting each substring by its corresponding factor. The resulting grammar is encoded by exploring some redundancies, such as common prefixes between suffix rules, which are sorted according to SAIS framework. When compared to well-known compression tools such as Re-Pair and 7-zip under repetitive sequences, our algorithm is faster at compressing and achieves compression ratio close to that of Re-Pair, at the cost of being the slowest at decompressing.

关键词： Grammar Sorting Production Encoding Arrays compression algorithms Adaptive arrays

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ECG Signal compression Using Wavelets. Preliminary Results

ECG Signal Compression Using Wavelets. Preliminary Results

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10th International Symposium on Signals, Circuits and Systems (ISSCS)

作者： Arvinti, Beatrice Nafornita, Corina Alexandru, Isar Costache, Marius Politehn Univ Dept Phys Fdn Engn Timisoara Romania Politehn Univ Commun Dept Elect & Telecommun Fac Timisoara Romania

ISBN: (纸本)9781457702013

The ECGs transmission problem becomes actual nowadays due to the tremendous progress in communications. One of the major aspects of the transmission is the source coding (compression). The wavelet theory becomes a tool frequently used in compression. The aim of this paper is a very fast compression algorithm based on wavelets. Some simulation results prove the performance of the proposed algorithm.

关键词： compression algorithms Discrete wavelet transforms ECG Electrocardiography Encoding Noise reduction Quantization Wavelet coefficients electrocardiography medical signal processing signal compression source coding source coding wavelet theory

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Multidimensional compression with Pattern Matching

Multidimensional Compression with Pattern Matching

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Data compression Conference (DCC)

作者： Del Guercio, Olivia Orozco, Rafael Sim, Alex Wu, Kesheng Scripps Coll Claremont CA 91711 USA Lawrence Berkeley Natl Lab Berkeley CA USA Bucknell Univ Lewisburg PA 17837 USA

ISBN: (纸本)9781728106571

Sensors typically record their measurements using more precision than the accuracy of the sensing techniques. Thus, experimental and observational data often contains noise that appears random and cannot be easily compressed. This noise increases storage requirement as well as computation time for analyses. In this work, we describe a line of research to develop data reduction techniques that preserve the key features while reduce the storage requirement. Our core observation is that the noise in such cases could be characterized by a small number of patterns based on statistical similarity. In earlier tests, this approach was shown to reduce the storage requirement by over 100-fold for one-dimensional sequences. In this work, we explore a set of different similarity measures for multidimensional sequences. During our tests with standard quality measures such as PSNR, we see that the new compression methods reduce the storage requirements over 100-fold while maintaining relatively low errors in peak signal-to-noise ratio. Thus, we believe that this is a new and effective way of constructing data reduction techniques.

关键词： Pattern matching Time measurement Data compression Dictionaries Heuristic algorithms compression algorithms Runtime

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Memory Efficient Lossless compression of Image Sequences with JPEG-LS and Temporal Prediction

Memory Efficient Lossless Compression of Image Sequences wit...

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29th Picture Coding Symposium (PCS)

作者： Wang, Zhe Chanda, Debasish Simon, Sven Richter, Thomas Univ Stuttgart Dept Parallel Syst Univ Str 38 D-70569 Stuttgart Germany Univ Stuttgart RUS Comp Ctr D-70550 Stuttgart Germany

ISBN: (纸本)9781457720482

In this paper, a lossless encoder for image sequences based on JPEG-LS defined for still images with temporal-extended prediction and context modeling is proposed. As embedded systems are one important field of application of the codec, on-line lossy reference frame compression is used to reduce the encoder's memory requirement. Variations of the pixel values in the reference frame due to lossy compression are acceptable since the predictor provides only estimations of the pixel values being encoded in the current frame. Larger variations decrease the final lossless compression performance of the encoder such that a trade-off between the memory requirement and the overall compression ratio is required. Different compression algorithms for the reference frame, including JPEG, JPEG 2000 and near-lossless JPEG-LS, and their impacts on the memory requirement and the overall lossless compression ratio have been studied. Experimental results show 9.6% or more gain in lossless compression ratio compared to applying the standard JPEG-LS frame-by-frame and 80% reduction in the encoder buffer size compared to storing the uncompressed reference frame.

关键词： REFERENCE FRAMES lossless compression memory requirements ENCODER image sequences compression ratio compression algorithms Context modeling JPEG lossy compression Still images codecs

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Selective compression Algorithm of Facial Images Based on DWT

Selective Compression Algorithm of Facial Images Based on DW...

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International Conference on Advanced Computer Theory and Engineering (ICACTE 2008)

作者： Lu Xiaoqi Zhang Baohua Inner Mongolia Univ Sci & Technol Sch Informat Engn Baotou City 014010 Mongolia

ISBN: (纸本)9780769534893

Image compression reduces time and cost in image storage without significant reduction of the image quality. This paper puts forward a wavelet-based predictive image coding algorithm, which has a higher coding rate than traditional coding algorithm. Based on the algorithm above, this article adopts the selective image compression technique to compress facial images. This algorithm attains a compression ratio from decade to several decades and settles the transmission and storage problem preferably.

关键词： compression algorithms Discrete wavelet transforms Image coding Frequency Wavelet transforms Predictive coding Wavelet analysis Image storage Humans Approximation algorithms

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A Low Complexity Image compression Algorithm for IoT Multimedia Applications 27

A Low Complexity Image Compression Algorithm for IoT Multime...

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27th European Signal Processing Conference (EUSIPCO)

作者： Campobello, Giuseppe Segreto, Antonino Univ Messina Dept Engn Messina Italy

ISBN: (纸本)9789082797039

This paper focuses on a novel lossless image compression algorithm which can be efficiently used for Internet of Things (IoT) multimedia applications. The proposed algorithm has low memory requirements and relies on a simple and efficient encoding scheme. Thus it can be easily implemented even in low-cost microcontrollers as those commonly used in several IoT platforms. Despite its simplicity, comparison results on different image datasets show that the proposed algorithm achieves compression ratios comparable with other more complex state-of-the-art solutions.

关键词： Image coding Signal processing algorithms compression algorithms Prediction algorithms Channel coding Internet of Things Gray-scale

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