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检索条件"主题词=Compression algorithms"

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Hierarchical compression of Tetrahedral Meshes Through Clustering and Vector Quantization

Hierarchical Compression of Tetrahedral Meshes Through Clust...

引用

IEEE Signal Processing and Communications Applications (SIU)

作者： Rizwan A. Siddiqui Serkan Eroksuz Isll Celasun Elektrik-Elektronik Fakültesi Elektronik ve Haberleğme Mühendisliği Bölümü İstanbul Teknik Üniversitesi Istanbul Turkey

To visualize the unstructured volumetric and surface data Delaunay triangulation is utilised which results in the formation of tetrahedral meshes. These generated tetrahedral meshes possessing Delaunay topology, facilitates the progressive transmission design and coding. Two or three levels of detail of the same data can be acquired by implementation of hierarchical decimation over these meshes. These data sets are then sent to Encoder for compression. A new scheme for geometry data compression has been devised in this paper. compression algorithm is composed of three stages. Initially centroids and the frequencies are determined by clustering. Then error vectors are generated by deducting vertex location from centroids. To exploit the statistical dependency of these error vectors vector quantization is employed over them in the third and final stage. The compression scheme, progressive transmission and quality of meshes are scalable.

关键词： Vector quantization Solid modeling Data visualization Topology Geometry Data compression compression algorithms Frequency

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A Parallel Decoder for Lossless Image compression by Block Matching

A Parallel Decoder for Lossless Image Compression by Block M...

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Data compression Conference (DCC)

作者： Luigi Cinque Sergio De Agostino Computer Science Department University of Roma La Sapienza Rome Italy

A work-optimal O(lognlogM) time PRAM-EREW algorithm for lossless image compression by block matching was shown in L. Cinque et al., (2003), where n is the size of the image and M is the maximum size of the match. The design of a parallel decoder was left as an open problem. By slightly modifying the parallel encoder, in this paper we show how to implement the decoder in O(lognlogM) time with O(n/logn) processors on the PRAM-EREW. With the realistic assumption that the size of the compressed image is O(n 1/2 ), the parallel decoder requires O(log 2 n) time and O(n/logn) processors on the mesh of trees

关键词： Decoding Image coding Remuneration Data structures Data compression Parallel algorithms Phase change random access memory compression algorithms

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ECG compression through segment matching and progressive error encoding

ECG Compression through segment matching and progressive err...

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

作者： M. Brito J. Henriques P. Carvalho B. Ribeiro M. Antunes CISUC Centre for Informatics and Systems University of Coimbra Portugal CCT-HUC Centre of Cardio-Thoracic Surgery University Hospital of Coimbra Portugal

This work describes a lossy electrocardiogram (ECG) compression algorithm based on R-R segmentation and segment matching. An ECG can be thought of as a quasi-periodic signal, with many similarities existing between heartbeats acquired from the same source. Through the use of an adaptive dictionary, it is possible to explore the similarities between new and previously encountered patterns, incorporating new patterns when a significant change in morphology has been observed. Algorithm simulation reveals very high compression ratios are possible on very regular signals.

关键词： Electrocardiography Encoding compression algorithms Dictionaries Switches Information systems Data compression Wavelet coefficients Matrix decomposition Heart beat

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A compression Method for Arbitrary Precision Floating-Point Images

A Compression Method for Arbitrary Precision Floating-Point ...

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IEEE International Conference on Image Processing

作者： Corey Manders Farzam Farbiz Steve Mann Institute of Infocomm Research Agency for Science Technology and Research Singapore Department of Electrical and Computer Engineering University of Toronto Toronto Canada

The paper proposes a method of compressing floating-point images of arbitrary precision. The concept of floating point images is used frequently in such areas as high dynamic range imaging, where pixel data stored as 8 or 12-bit integers are insufficient. The compression scheme presented in the paper organizes the floating point data in a manner such that already existing compression algorithms such as JPEG or Zlib compression may be used once the data re-organization has taken place. The paper compares the result to a popular (but restrictive) form of image compression, openEXR, and shows significant gains over this format. Furthermore, the compression scheme presented is scalable to deal with floating point images of arbitrary precision.

关键词： Image coding Dynamic range Layout Displays Cameras Educational institutions Application software Pixel compression algorithms Transform coding

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Integrating Memory compression and Decompression with Coherence Protocols in Distributed Shared Memory Multiprocessors

Integrating Memory Compression and Decompression with Cohere...

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International Conference on Parallel Processing (ICPP)

作者： Lakshmana Rao Vittanala Mainak Chaudhuri Intel Technology India Private Limited Bangalore India Department of Computer Science and Engineering Indian Institute of Technology Kanpur India

Ever-increasing memory footprint of applications and increasing mainstream popularity of shared memory parallel computing motivate us to explore memory compression potential in distributed shared memory (DSM) multiprocessors. This paper for the first time integrates on-the-fly cache block compression/decompression algorithms in the cache coherence protocols by leveraging the directory structure already present in these scalable machines. Our proposal is unique in the sense that instead of employing custom compression/decompression hardware, we use a simple on-die protocol processing core in dual-core nodes for running our directory-based coherence protocol suitably extended with compression/decompression algorithms. We design a low-overhead compression scheme based on frequent patterns and zero runs present in the evicted dirty L2 cache blocks. Our compression algorithm examines the first eight bytes of an evicted dirty L2 block arriving at the home memory controller and speculates which compression scheme to invoke for the rest of the block. Our customized algorithm for handling completely zero cache blocks helps hide a significant amount of memory access latency. Our simulation-based experiments on a 16-node DSM multiprocessor with seven scientific computing applications show that our best design achieves, on average, 16% to 73% storage saving per evicted dirty L2 cache block for four out of the seven applications at the expense of at most 15% increased parallel execution time.

关键词： Protocols Hardware compression algorithms Scientific computing Parallel processing Computational modeling Computer architecture Airports Computer science Application software

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Lossless compression of Hyperspectral Imagery Using Integer Principal Component Transform and 3-D Tarp Coder

Lossless Compression of Hyperspectral Imagery Using Integer ...

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ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD)

作者： Xin Luo Lei Guo Zhen Liu College of Automation Northwestern Polytechnical University China School of Automation and Engineering University of Electronic Science and Technology China

Based on factorization of the transform matrix in triangular elementary reversible matrices (TERM), an integer approximation algorithm of the principal component transform (IPCT) is proposed. We improve the pivoting method of TERM factorization in order to obtain limited error and enhanced computational efficiency, and we develop a new lossless compression algorithm for hyperspectal imagery combining the perfectly reversible integer PCT with the 3-D Tarp coder. After applying an integer wavelet transform in spatial domain we use the improved IPCT for inter-band derecolation. In coding stage the novel 3-D Tarp coder allows probability estimation with five simple recursive filters. And this probability estimate can be used to drive a non-adaptive arithmetic coder to entropy code significance-map and refinement information of transformed coefficients. The main advantage of our compression algorithm is low complexity and it can yield embedded bitstreams with higher compression ratio compared to existing algorithms.

关键词： Image coding Hyperspectral imaging compression algorithms Approximation algorithms Computational efficiency Wavelet domain Wavelet transforms Recursive estimation Filters Arithmetic

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An Efficient compression Algorithm for Hyperspectral Images Based on Correlation Coefficients Adaptive Three Dimensional Wavelet Zerotree Coding

An Efficient Compression Algorithm for Hyperspectral Images ...

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IEEE International Conference on Image Processing

作者： Guizhong Liu Fan Zhao School of Electronic and Information Engineering Xi'an Jiaotong University Xi'an China

In this paper, we propose an efficient compression algorithm for hyperspectral images. It is based on the correlation coefficients adaptive AT-3DSPIHT coding in the domain of WPT (wavelet packet transform). According to the characteristics of correlation coefficients between spectral bands, a binary tree spectral band grouping algorithm is carried out to divide the adjacent spectral bands into different mode groups. Along with this, WPT with the corresponding decomposition levels and a proper AT-3D zerotree are determined adaptively. Several AVIRIS images are used to evaluate the proposed algorithm. Compared with the existing 3D-based algorithms, the proposed adaptive AT-3DSPIHT achieves the best compression performance at lower rates. Moreover, at the low correlated adjacent bands, our proposed algorithm also beats the 2DSPIHT and JPEG2000-MC algorithm respectively.

关键词： compression algorithms Hyperspectral imaging Image coding Binary trees Wavelet transforms Clustering algorithms Wavelet packets Wavelet domain Satellite ground stations Downlink

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A Three-Step Nonlinear Lifting Scheme for Lossless Image compression

A Three-Step Nonlinear Lifting Scheme for Lossless Image Com...

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IEEE International Conference on Image Processing

作者： Gemma Piella Beatrice Pesquet-Popescu Technology Department Universitat Pompeu Fabra Barcelona Spain Signal and Image Proc. Department GET-ENST Paris France

We propose an adaptive wavelet transform that results in fewer large detail coefficients while preserving image contours in the approximation subband. The transform is constructed with a three-step nonlinear lifting scheme: a fixed prediction followed by a space-varying update and a non-additive prediction. The interest of the proposed scheme is demonstrated for nearly lossless compression.

关键词： Image coding Wavelet transforms Decorrelation Nonlinear filters Space technology Adaptive signal processing Nonlinear systems Signal processing algorithms Transform coding compression algorithms

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Integer Polar Coordinates for compression

Integer Polar Coordinates for Compression

引用

IEEE International Symposium on Information Theory

作者： Demba E. Ba Vivek K Goyal Massachusetts Institute of Technology USA

ISBN: (纸本)9781424413973;1424413974

This paper introduces a family of integer-to-integer approximations to the Cartesian-to-polar coordinate transformation and analyzes its application to lossy compression. A high-rate analysis is provided for an encoder that first uniformly scalar quantizes, then transforms to "integer polar coordinates," and finally separately entropy codes angle and radius. For sources separable in polar coordinates, the performance (at high rate) is shown to match that of entropy-constrained unconstrained polar quantization - where the angular quantization is allowed to depend on the radius. Thus, for sources separable in polar coordinates but not separable in rectangular coordinates - including certain Gaussian scale mixtures - the proposed system performs better than any transform code. Furthermore, unlike unconstrained polar quantization, integer polar coordinates are appropriate for lossless compression of integer-valued vectors. Combination of integer polar coordinates with integer-to-integer transform coding is also discussed.

关键词： Quantization Transform coding Discrete wavelet transforms Gaussian processes Entropy coding Testing Performance evaluation compression algorithms Video coding Karhunen-Loeve transforms

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High Throughput compression of Double-Precision Floating-Point Data

High Throughput Compression of Double-Precision Floating-Poi...

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Data compression Conference (DCC)

作者： Martin Burtscher Paruj Ratanaworabhan School of Electrical and Computer Engineering Cornell University Ithaca NY USA

This paper describes FPC, a lossless compression algorithm for linear streams of 64-bit floating-point data. FPC is designed to compress well while at the same time meeting the high throughput demands of scientific computing environments. On our thirteen datasets, it achieves a substantially higher average compression ratio than BZIP2, DFCM, FSD, GZIP, and PLML At comparable compression ratios, it compresses and decompresses 8 to 300 times faster than the other five algorithms

关键词： Throughput Flexible printed circuits compression algorithms Encoding Data engineering Scientific computing Computer crashes Writing Data compression Counting circuits

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