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检索条件"主题词=Compression algorithms"

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Tree Partitioning compression of Piecewise Polynomial Functions

Tree Partitioning Compression of Piecewise Polynomial Functi...

引用

Asilomar Conference on Signals, Systems & Computers

作者： Arian Maleki Morteza Shahram Department of Electrical Engineering University of Stanford USA

In this paper compression of piecewise polynomial functions is considered. The importance of this class of functions is due to the fact that most of the signals observed in the nature are piecewise smooth and piecewise polynomials provide an efficient model for representing piecewise smooth signals. We compute the e-entropy of the class of piecewise polynomials and show that the rate-distortion behavior of the traditional compression algorithms is far from optimum. Then we will discuss the binary partitioning algorithm, and will demonstrate that with a simple modification of this algorithm, it is possible to get close to the optimal performance. Moreover, this modification will retain all the advantages of the binary tree algorithms such as simplicity, automatic parameter selection and extension to higher dimensions.

关键词： Polynomials Partitioning algorithms Rate-distortion Binary trees Image coding Dynamic programming Statistics compression algorithms Bit rate Stochastic processes

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Texture characterization and compression based on human perception in the JPEG2000 framework

Texture characterization and compression based on human perc...

引用

IEEE International Conference on Image Processing

作者： G. Fahmy J. Black S. Panchanathan Lane Department of Computer Science and Electrical Engineering West Virginia University USA Kesearch Center for Ubiquitous Computing Cubic Department of Computer Science and Engineering Arizona State University USA

Over the last decade perceptually based image compression has gained significant importance. This is because it relies on Human Visual Perception (HVP) in measuring the reconstruction quality in the compression process, as humans are the end users for images. Visual data that is perceived by humans can be characterized in terms of three parameters. Magnitude, Phase and Orientation of the spatial frequency content. While existing perceptually based image compression techniques exploits the first parameter, the novel contribution of this paper is its focus on the use of phase data for perceptually based texture compression. In this paper a HVS based texture characterization approach is applied to measure the perceived (by humans) phase coherence in the image. Then images are more compressed after removing the unperceived phase redundancy. Finally subjective tests are performed to measure the reconstruction quality of the proposed compression approach. The proposed compression algorithm has been applied in the JPEG2000 framework. Simulation results that demonstrate the efficiency of the proposed approach are presented.

关键词： Humans Transform coding Image coding Image reconstruction Visual perception Frequency Phase measurement Testing Performance evaluation compression algorithms

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MLC: An Efficient Multi-level Log compression Method for Cloud Backup Systems

MLC: An Efficient Multi-level Log Compression Method for Clo...

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IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

作者： Bo Feng Chentao Wu Jie Li Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China Department of Computer Science University of Tsukuba Tsukuba Ibaraki Japan

ISBN: (纸本)9781509032068

With the rapid development of Internet and cloud services, logs become one of the fastest growing data types in backup storage systems. These massive data always require long-term storage, which incurs high storage overhead. Typical compression algorithms, such as traditional lossless compression and log-specific compression algorithms, are employed to increase storage efficiency. However, these algorithms ignore the inherent semantics of logs, particularly for the well-structured compositions within log records and the striking similarities among them. Therefore, they cannot guarantee a satisfactory compression ratio. To address this problem, we propose a novel Multi-level Log compression (MLC) method for cloud backup systems. MLC can achieve high compression ratio for various applications and workloads. Different from existing compression algorithms, MLC first explores data redundancy among log records and divides them into different buckets in accordance with their similarities. Then, the log records are condensed by a variation of delta compression. After that, a traditional compression algorithm is employed as the secondary compression to further improve the compression ratio. To demonstrate the effectiveness of MLC, we conduct several experiments under different log workloads. The results show that, MLC improves the compression ratio of 7zip, gzip and bzip2 by up to 30.3%, 26.8% and 16.1%, respectively.

关键词： compression algorithms Cloud computing Semantics Indexes Redundancy Algorithm design and analysis Computer science

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Customizable compression Architecture for Efficient Configuration in CGRAs

Customizable Compression Architecture for Efficient Configur...

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Annual IEEE Symposium on Field-Programmable Custom Computing Machines (FCCM)

作者： Syed M.A.H. Jafri Adeel Tajammul Masoud Daneshtalab Ahmed Hemani Kolin Paul Peeter Ellervee Juha Plosila Hannu Tenhunen Turku Centre for Computer Science Royal Institute of Technology Sweden University of Turku Finland Indian Institute of Technology Delhi Tallin University of Technology Estonia

Today, Coarse Grained Reconfigurable Architectures (CGRAs) host multiple applications. Novel CGRAs allow each application to exploit runtime parallelism and time sharing. Although these features enhance the power and silicon efficiency, they significantly increase the configuration memory overheads. As a solution to this problem researchers have employed statistical compression, intermediate compact representation, and multicasting. Each of these techniques has different properties, and is therefore best suited for a particular class of applications. However, existing research only deals with these methods separately. In this paper we propose a morphable compression architecture that interleaves these techniques in a unique platform.

关键词： Computer architecture Multicast communication Software Hardware Educational institutions Silicon compression algorithms

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Multilayer document compression algorithm

Multilayer document compression algorithm

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IEEE International Conference on Image Processing

作者： Hui Cheng C.A. Bouman School of Electrical and Computer Engineering Purdue University West Lafayette IN USA

In this paper, we propose a multilayer document compression algorithm. This algorithm first segments a scanned document image into different classes such as text, images and background, then compresses each class using an algorithm specifically designed for that class. Two algorithms are investigated for segmenting documents: a general purpose image segmentation algorithm called the trainable sequential MAP (TSMAP) algorithm, and a rate-distortion optimized segmentation (RDOS) algorithm. Experimental results show that the multilayer compression algorithm can achieve a much lower bit rate than most conventional algorithms such as JPEG at similar subjective distortion levels. We also find that the RDOS method produces more robust segmentations than TSMBP by eliminating misclassifications which can sometimes cause severe artifacts.

关键词： Nonhomogeneous media compression algorithms Image segmentation Graphics Spatial resolution Image coding Algorithm design and analysis Bit rate Transform coding Robustness

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Lossless and near-lossless image compression based on multiresolution analysis

Lossless and near-lossless image compression based on multir...

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IEEE International Conference on Image Processing

作者： F. Arandiga Departament de Matemàtica Aplicada Universitat de València Spain

Being able to control the quality of the decoded data instead of the compression rate is suitable for applications where quality control is of utmost importance, yet we would like to be as economical as possible with respect to storage and speed of computation. In this paper we present a compression algorithm based on Harten's interpolatory framework for multiresolution that guarantees a specific estimate of the error between the original and the decoded image measured in the max-norm.

关键词： Image coding Multiresolution analysis Decoding Biomedical imaging Quantization Quality control compression algorithms Image resolution Remote sensing Digital photography

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UdeAlignC: Fast Alignment for the compression of DNA Reads

UdeAlignC: Fast Alignment for the Compression of DNA Reads

引用

IEEE Colombian Communications Conference (COLCOM)

作者： Jaime Lotero Andrés Benavides Aníbal Guerra Sebastián Isaza Facultad de Ingeniería Universidad de Antioquia UdeA Calle 70 No. 52-21 Medellín Colombia Facultad de Ciencias y Tecnología FaCyT Universidad de Carabobo UC Valencia Venezuela

Referential compression algorithms are one of the main strategies to cope with the exponential growth of DNA data available to scientists. One of the techniques used to build a referential compression is sequence alignment, which in turn requires a lot of computing. In this article we present UdeAlignC, a fast alignment algorithm for the compression of DNA reads. We demonstrate that our algorithm is 2× faster than prominent state of the art tools while optimality is only reduced by 5.6%. We also implement a GPU-accelerated version and show local speedups of up to 12×. Source code available at https://***/BioMRcomp/udealignc.

关键词： DNA Tools Sensitivity Sequential analysis compression algorithms Indexes Graphics processing units

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An improved WSQ fingerprint image compression algorithm

An improved WSQ fingerprint image compression algorithm

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Asilomar Conference on Signals, Systems & Computers

作者： Jinshan Tang Xiaoming Liu College of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Image Processing and Bio-Imaging Reasearch Laboratory Systems Research Institute Department of Advanced Technologies Alcorn State University Lorman MS USA

The wavelet/scalar quantization (WSQ) [1] fingerprint image compression algorithm is effective and has been widely applied to fingerprint image compression. However, WSQ cannot control the compression ratio and its performance on fuzzy images is poor. We propose an improved WSQ fingerprint image compression algorithm to overcome the above shortcomings. Our algorithm uses a mixed quantizer so that the algorithm can treat fuzzy and non-fuzzy fingerprint images separately. In order to control the compression ration, an optimization parameters for a specific compression ratio. The proposed algorithm is compared with the traditional WSQ fingerprint image compression algorithm and the results are encouraging.

关键词： Fingerprint recognition Image matching compression algorithms

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A new data compression technique for electrocardiograms

A new data compression technique for electrocardiograms

引用

International Biomedical Engineering Days

作者： M. Evin M. Korurek Electr. & Electron. Eng. Fac. Tech. Univ. of Istanbul Turkey Electrical and Electronics Engineering Faculty Technical University Istanbul Istanbul Turkey

A new approach for real-time ECG data compression is presented. This technique is a hybrid of well known techniques called SAPA-2 and Adaptive compression algorithm. A special decompression algorithm and smooth-curve approximation are used to reconstruct the compressed data into original form. In order to compare this new approach on the same bases with other well known techniques which are widely used in practice, all the techniques are applied to the same single lead ECG signal.< >

关键词： Data compression Electrocardiography compression algorithms Approximation algorithms Signal processing Rhythm Data handling Data engineering Clinical diagnosis Costs

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compression Schemes for Similarity Queries

Compression Schemes for Similarity Queries

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Data compression Conference (DCC)

作者： Idoia Ochoa Amir Ingber Tsachy Weissman Dept. of Electrical Engineering Stanford University Stanford CA

ISBN: (纸本)9781479934188

We consider compression of sequences in a database so that similarity queries can be performed efficiently in the compressed domain. The fundamental limits for this problem setting, which characterize the trade off between compression rate and reliability of the answers to the queries, have been characterized in past work. However, how to approach these limits in practice has remained largely unexplored. Recently, we proposed a scheme for this task that is based on existing lossy compression algorithms, for the general case where the similarity measure satisfies a triangle inequality. Although it was shown that it achieves the fundamental limits for some cases, it is suboptimal in general. In this paper we propose a new scheme that also uses lossy compression algorithms as a building block, but with a carefully chosen distortion measure that is different than the one defining the similarity between sequences. The new scheme significantly improves the compression rate compared to the previously proposed scheme in many cases. For example, for binary sources and Hamming similarity measure, simulation results show a compression rate close to the fundamental limit, and an improvement over the previously proposed scheme of up to 55% (for the same reliability). The results shed light on the fact that compression for similarity identification is inherently different than classical lossy compression.

关键词： Databases Distortion measurement Loss measurement compression algorithms Reliability Vectors Random variables

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