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检索条件"主题词=Compression algorithms"

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Lossless image compression using kernel based Global Structure Transform (GST)

Lossless image compression using kernel based Global Structu...

引用

International Conference on Emerging Technologies, ICET

作者： M. Asif Ali Aftab Khan M. Younus Javed Aasia Khanum Department of Computer Engineering College of Electrical & Mechanical Engineering National University of Science and Technology Islamabad Pakistan

Lossless data compression using the variants of Burrows-Wheeler Transform (BWT) with various compression encoders has proven its effectiveness. This research provides a unique method for lossless compression of color images by improving the Global Structure Transform (GST) stage of the Burrows-Wheeler compression Algorithm (BWCA). The proposed model applies the Move-To-Front (MTF) transform at the GST stage by selecting 2-D block (kernel) of BWT data. This method has resulted in a high occurrence of same gray levels in the kernel. Moreover, the symbol map for the MTF Encoder is generated only for the available gray levels in the kernel. The overall redundancy of the MTF indexes increases at the GST stage of the BWCA which results in increased compression.

关键词： Kernel Image coding Transforms Encoding compression algorithms Indexes Data compression

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A skip-line with threshold algorithm for binary image compression

A skip-line with threshold algorithm for binary image compre...

引用

Congress on Image and Signal Processing, CISP

作者： Hao Sung Wen-Yan Kuo Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan Department of Computer Science and Information Engineering FuJen Catholic University Taipei Taiwan

Binary images (Bi-level images; Bi-Color images, Two-tone images or Monochrome images) have been widely used in image processing, such as facsimile, letters, map archives, digital libraries, fingerprint databases, and those documents that could not be recognized by OCR. In order to reduce the storage space of binary images, there are many researchers attempted to propose more efficient algorithms for binary image compression. In general, they can be divided into two kinds of methods which are `lossless' and `lossy'. In this research, we base on a lossy image compression method, to propose a compression Algorithm called “Skip-Line Encoding with Threshold” (SLETA). Our results of experiments show that SLETA not only achieve high compression ratio but also keep good recognizability: encoded images are not difficult to recognize after decompressions.

关键词： Image coding Correlation Encoding compression algorithms Transform coding Distance measurement Image recognition

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Algorithm for DNA sequence compression based on prediction of mismatch bases and repeat location

Algorithm for DNA sequence compression based on prediction o...

引用

IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)

作者： Kalyan Kumar Kaipa Ajit S Bopardikar Srikantha Abhilash Parthasarathy Venkataraman Kyusang Lee Taejin Ahn Rangavittal Narayanan SAIT India Laboratory Samsung Bangalore India SAIT Samsung Electronics Company Limited Suwon South Korea

For DNA sequence compression, it has been observed that methods based on Markov modeling and repeats give best results. However, these methods tend to use uniform distribution assumption of mismatches for approximate repeats. We show that these replacements are not uniformly distributed and we can improve compression efficiency by using non uniform distribution for mismatches. We also propose a hash table based method to predict repeat location which works well for block based genomic sequence compression algorithms. The proposed methods give good compression gains. The method can be incorporated into any algorithm that uses approximate repeats to realize similar gains.

关键词： Prediction algorithms Encoding DNA Electronic mail Markov processes compression algorithms Approximation algorithms

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Improved Rice Algorithm of Lossless compression for On-Board Images

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

引用

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?

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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...

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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...

引用

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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