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检索条件"主题词=Compression algorithms"

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Improved Rice Algorithm of Lossless compression for On-Board Images

Improved Rice Algorithm of Lossless Compression for On-Board...

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International Conference on Multimedia Technology

作者： Yong-wang Wei Qing-hai Ding Hai-bo Luo Shenyang Institute of Automation Key Laboratory of Optical-Electronics Information Processing Chinese Academy and Sciences Shenyang China Electrical and Information Engineering College Beihang University Jilin China Chinese Academy and Sciences Beijing China Institut für Informatik Ludwig-Maximilians-Universität München

Aiming at the problems of the relatively lower compression ratio and the difficulty in hardware implementation regarding Rice lossless compression algorithm for the Space-borne Remote-sensing images, an improved Rice method is proposed in which the length of predictor FIFO is determined by the size of input images and the global unicode for differences is used. The improved Rice algorithm is mainly composed of two steps, MED prediction for the whole row data and Rice global uniform entropy coding. The statistical results show that it can significantly reduce the spatial redundancy of the adjacent pixels and the mean value of image differences. The compression bit rate is reduced approximately 0.4581 bpp(bit/pixel) against the original Rice algorithm. Furthermore, the new way reserves the all detail information of the input images throughout the whole encoding process. Because we split the all samples with the same mode, the proportion of the identifier of the splitting mechanic in the output data stream is reduced and the compression ratio is increased. The improvement can reduce the encoding complexity and be easily implemented for hardware application.

关键词： Image coding Manganese Pixel Laboratories Prediction algorithms compression algorithms Remote sensing

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EEG compression using JPEG2000: How much loss is too much?

EEG compression using JPEG2000: How much loss is too much?

引用

Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Garry Higgins Stephen Faul Robert P. McEvoy Brian McGinley Martin Glavin William P. Marnane Edward Jones College of Engineering and Informatics National University of Ireland Galway Ireland Department of Electrical & Electronic Engineering University College Cork Cork Ireland

compression of biosignals is an important means of conserving power in wireless body area networks and ambulatory monitoring systems. In contrast to lossless compression techniques, lossy compression algorithms can achieve higher compression ratios and hence, higher power savings, at the expense of some degradation of the reconstructed signal. In this paper, a variant of the lossy JPEG2000 algorithm is applied to Electroencephalogram (EEG) data from the Freiburg epilepsy database. By varying compression parameters, a range of reconstructions of varying signal fidelity is produced. Although lossy compression has been applied to EEG data in previous studies, it is unclear what level of signal degradation, if any, would be acceptable to a clinician before diagnostically significant information is lost. In this paper, the reconstructed EEG signals are applied to REACT, a state-of-the-art seizure detection algorithm, in order to determine the effect of lossy compression on its seizure detection ability. By using REACT in place of a clinician, many hundreds of hours of reconstructed EEG data are efficiently analysed, thereby allowing an analysis of the amount of EEG signal distortion that can be tolerated. The corresponding compression ratios that can be achieved are also presented.

关键词： Electroencephalography Transform coding Image coding Databases compression algorithms Epilepsy Wireless communication

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Framework for Energy-Aware Lossless compression in Mobile Services: The Case of E-Mail

Framework for Energy-Aware Lossless Compression in Mobile Se...

引用

IEEE International Conference on Communications (ICC)

作者： Y. Xiao M. Siekkinen A. Ylä-Jääski Department of Computer Science and Engineering Aalto University Espoo Finland

Energy consumption caused by wireless transmission poses a big challenge to the battery lifetime of mobile devices. While the potential of using lossless compression for saving energy has been long acknowledged, no general solution has been proposed for applying lossless compression to energy adaptation for mobile services. We propose a proxy-based energy adaptation framework, in which the data to be transmitted is losslessly compressed on a proxy server according to context-aware policies. The context includes factors relevant to computational and communication cost, as well as the user's preferences. We showcase a context-aware policy which aims at minimizing clientside energy consumption caused by transmission and decompression. Using our framework, we implement an energy-aware mobile e-mail service, and present power measurement results that show significant energy savings.

关键词： Mobile communication Computational efficiency Context compression algorithms Energy consumption Costs Mobile computing Decision making Throughput Data communication

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FPGA-based lossless compressors of floating-point data streams to enhance memory bandwidth

FPGA-based lossless compressors of floating-point data strea...

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International Conference on Application Specific Systems (ASAP), Architectures and Processors

作者： Kazuya Katahira Kentaro Sano Satoru Yamamoto School of Information Sciences University of Tohoku Sendai Japan

This paper presents an FPGA-based lossless compressor which directly compresses floating-point data streams to enhance the actual memory bandwidth of lattice Boltzmann method (LBM) accelerators. We show that the compression algorithms based on the 1D polynomial prediction are suitable for high-throughput hardware design. Moreover we show that integer operations provide comparable prediction performance to a floating-point predictor, while an integer predictor is expected to have smaller circuits than a floating-point one. We evaluate the compression ratio, the operating frequency and the resource consumption of the compressors with integer-based predictors through their prototype implementation using ALTERA Stratix III FPGA. We demonstrate that the implemented compressors dominate only 0.15 to 0.23 % of the entire logic resources and operate at 95 to 174 MHz to provide the compression ratio of up to 3.5, which means that we can enhance the memory bandwidth by a factor of 3.5 on average.

关键词： Compressors Bandwidth Lattice Boltzmann methods compression algorithms Polynomials Hardware Algorithm design and analysis Circuits Frequency Prototypes

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Development of the grooming techniques for reducing network traffic in sensor networks

Development of the grooming techniques for reducing network ...

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International Conference on Wireless Communication and Sensor Networks

作者： R. K. Kushwaha S. Kar Electrical Engineering Indian Institute of Technology Delhi New Delhi India

Sensor networks are widely used in environmental exploration, military systems, and factory production monitoring. They usually have limited battery source and link bandwidth. Many algorithms have been proposed till now that considered three functional components namely data gathering (sensing and acquisition), data transport and data analysis (processing). In general power is consumed whenever a bit is generated, transmitted or processed. So, various network architectures and different protocols have been proposed for saving energy consumption and extending the life time of sensor node. Our aim, therefore, is to reduce the number of bits to be transported to achieve energy efficiency. This can be done by recognizing the type of stream data, compression based on the source and grooming/aggregation of the traffic. So, we have developed a compression algorithm which is based on identified distribution of sensed stream data of source which aims to reduce network traffic in order to save power by combining both compression algorithm and state model.

关键词： compression algorithms Wireless sensor networks Loss measurement Computer architecture Humidity Clustering algorithms Dictionaries

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Finding approximate frequent patterns in streaming medical data

Finding approximate frequent patterns in streaming medical d...

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Annual IEEE Symposium on Computer-Based Medical Systems

作者： Jessica Lin Yuan Li Computer Science Department George Mason University Fairfax VA USA

Time series data is ubiquitous and plays an important role in virtually every domain. For example, in medicine, the advancement of computer technology has enabled more sophisticated patients monitoring, either on-site or remotely. Such monitoring produces massive amount of time series data, which contain valuable information for pattern learning and knowledge discovery. In this paper, we explore the problem of identifying frequently occurring patterns, or motifs, in streaming medical data. The problem of frequent patterns mining has many potential applications, including compression, summarization, and event prediction. We propose a novel approach based on grammar induction that allows the discovery of approximate, variable-length motifs in streaming data. The preliminary results show that the grammar-based approach is able to find some important motifs in some medical data, and suggest that using grammar-based algorithms for time series pattern discovery might be worth exploring.

关键词： Time series analysis Grammar Approximation algorithms Algorithm design and analysis Data mining Probabilistic logic compression algorithms

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NO-REFERENCE IMAGE SHARPNESS ASSESSMENT BASED ON LOCAL PHASE COHERENCE MEASUREMENT

NO-REFERENCE IMAGE SHARPNESS ASSESSMENT BASED ON LOCAL PHASE...

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IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： Rania Hassen Zhou Wang Magdy Salama Dept. of Electrical and Computer Engineering University of Waterloo Waterloo Ontario Canada

ISBN: (纸本)9781424442959

Sharpness is one of the most determining factors in the perceptual assessment of image quality. Objective image sharpness measures may play important roles in the design and optimization of visual perception-based auto-focus systems and image enhancement, restoration and compression algorithms. Here we propose a new sharpness measure where sharpness is identified as strong local phase coherence evaluated in the complex wavelet transform domain. Our test using the LIVE blur database shows that the proposed algorithm correlates well with subjective quality evaluations. An additional advantage of our approach is that other image distortions such as compression, median filtering and noise contamination that may affect perceptual sharpness can also be detected.

关键词： perceptual image quality image sharpness image blur no-reference image quality assessment local phase coherence complex wavelet transform complex wavelet transform image blur Sharpness SHARPNESS OF IMAGE phase coherence Sound contamination compression algorithms IMAGE DISTORTION quality evaluation

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LifeStream: Real-Time Bio-Signal Remote Monitoring System

LifeStream: Real-Time Bio-Signal Remote Monitoring System

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The 4th International Conference on Bioinformatics and Biomedical Engineering(第四届IEEE生物信息与生物医学工程国际会议 iCBBE 2010)

作者： P.Carvalho L.Vale J.Henriques M.Brito A.Pena F.Santiago Centre for Informatics and Systems University of Coimbra Coimbra Portugal Applied Research and Knowledge Dissemination Portugal Telecom Inovacao S.A.Aveiro Portugal

This paper describes the design of a modular solution for remote bio-signal monitoring and processing. The main purpose is to increase health care efficiency by providing critical and intensive care units with lack of specialized personnel with access to off-site specialized patient diagnosis and therapeutic indications. The system modularity allows the integration of specific processing modules, such as diagnostic or compression algorithms. This solution was integrated into an existing telemedicine platform developed by Portugal Telecom. Currently the system is used to support professionals’ decision support workflow concerning the transfer of critically ill paediatric patients between hospitals. Moreover, it introduces automation and mobile monitoring mechanisms in the process of transport of patients to specialized medical facilities that can be exploited into the future.

关键词： Real time systems Remote monitoring Patient monitoring Medical services Personnel Medical diagnosis compression algorithms Telemedicine Telecommunications Pediatrics

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Compressing Floating-Point Number Stream for Numerical Applications

Compressing Floating-Point Number Stream for Numerical Appli...

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International Conference on Networking and Computing (ICNC)

作者： Hisanobu Tomari Mary Inaba Kei Hiraki Graduate School of Information Science and Technology University of Tokyo Tokyo Japan

A cluster of commodity computers and general-purpose computers with accelerators such as GPGPUs are now common platforms to solve computationally intensive tasks like scientific simulations. Both technologies provide users with high performance at relatively low cost. However, the low bandwidth of interconnect compared to the computing performance hinders efficient operation of both cluster and accelerator in the case of many algorithms that require heavy data transmission. For clusters the network is one of the major performance bottlenecks, and for accelerators the peripheral bus to transfer data from host to the memory on the accelerator card is. In this paper, we propose a method of accelerating the performance of floating-point intensive algorithms by compressing the floating point number stream. With the efficient software encoder and hardware decoder, the method eliminates redundancy in the exponential part in the array of numbers on the stream and compacts the entire array to 82.8% of its original size at theoretical limit. The compression ratio is better than Gzip or Bzip2 for floating point numbers. The reduction in communication time directly leads to the reduction in total application running time for programs whose processing time is largely dominated by communication performance. We implemented a high-speed decoder using FPGA that operates at over 6 GB/s. We estimated the application performance using FFT and matrix multiplication on a cluster and the GRAPE-DR accelerator respectively, and our approach is useful in both configurations.

关键词： Decoding Pipelines History Hardware compression algorithms Computers Computational modeling

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Optimum String Match Choices in LZSS

Optimum String Match Choices in LZSS

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Data compression Conference (DCC)

作者： Graham Little James Diamond Jodrey School of Computer Science Acadia University Wolfville NS Canada

ISBN: (纸本)9781424464258;9780769539942

compression techniques in the LZ77 family operate by repeatedly searching for strings in a dictionary and then outputting a series of tokens which unambiguously define the chosen sequence of strings. The dictionary is composed of the most-recently matched N symbols, for some implementation-dependent N. The strings to be matched are the prefixes of the remaining input symbols. When a particular prefix has been matched, those symbols are moved from the beginning of the remaining symbols to the end of the dictionary; in general this will cause some symbols to be deleted from the beginning of the dictionary, in order to limit its size to N. compression algorithms in the LZ77 family perform a greedy choice when looking for the next string of input symbols to match. That is, the longest string of symbols which is found in the current dictionary is chosen as the next match. Many variations of LZ77 have been proposed; some of these attempt to improve compression by sometimes choosing a non-maximal string, if it appears that such a choice might improve the overall compression ratio. In this paper we present an algorithm which computes a set of matches designed to minimize the number of bits output, not necessarily the number of strings matched. In some variants of LZ77, the token stream is itself compressed using a statistical technique, which means the length of a token is not known a priori. However, other LZ77 variants code the tokens using a scheme for which the length of a given token can be computed in advance. In such a case it is computationally feasible to compute the globally optimum set of matches (we refer to this as the optimum parsing of the input). The basic idea is as follows. At each step of the compression process, the number of bits required by an optimum parsing of the input ending at the current position is known. If the longest match available at this point has length m, then candidate optimum parsings for each of the next m positions can be computed by

关键词： Dictionaries Data compression Computer science compression algorithms Impedance matching Algorithm design and analysis Testing Councils

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