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检索条件"主题词=Compression algorithms"

共 2075 条记录，以下是491-500 订阅

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Fast texture synthesis using tree-structured vector quantization 00

Fast texture synthesis using tree-structured vector quantiza...

引用

Computer Graphics Annual Conference

作者： Wei, LY Levoy, M Stanford Univ Stanford CA 94305 USA

ISBN: (纸本)1581132085

Texture synthesis is important for many applications in computer graphics, vision, and image processing. However, it remains difficult to design an algorithm that is both efficient and capable of generating high quality results. In this paper, we present an efficient algorithm for realistic texture synthesis. The algorithm is easy to use and requires only a sample texture as input. It generates textures with perceived quality equal to or better than those produced by previous techniques, but runs two orders of magnitude faster. This permits us to apply texture synthesis to problems where it has traditionally been considered impractical. In particular, we have applied it to constrained synthesis for image editing and temporal texture generation. Our algorithm is derived from Markov Random Field texture models and generates textures through a deterministic searching process. We accelerate this synthesis process using tree-structured vector quantization.

关键词： processing texture synthesis compression algorithms image processing

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Optimal transform coding of Gaussian mixtures for joint classification/reconstruction

Optimal transform coding of Gaussian mixtures for joint clas...

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Data compression Conference 2003 (DCC2003)

作者： Jana, S Moulin, P Univ Illinois Beckman Inst Coordinate Sci Lab Urbana IL 61801 USA

ISBN: (纸本)0769518966

In a variety of applications, classification systems operate on compressed signals. This paper explores the design of optimal transform coders optimizing a joint classification/reconstruction criterion, where classification accuracy is measured using the Chernoff bound on probability of misclassification and reconstruction quality is measured using mean-squared error (MSE) distortion. Under a high-rate assumption, we show local optimality properties of the Karhunen-Loeve transform (KLT) for a certain class of Gaussian mixtures under a joint classification/MSE measure, and derive analytical expressions for optimal bit-allocation. This generalizes classical optimality properties of the KLT for Gaussian sources under the MSE criterion.

关键词： Bit rate compression algorithms Data compression Decorrelation Design optimization Distortion measurement Image coding Image reconstruction Karhunen-Loeve transforms Transform coding

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A new near-lossless image compression algorithm suitable for hardware design in wireless endoscopy system

A new near-lossless image compression algorithm suitable for...

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IEEE International Conference on Image Processing

作者： Xiang Xie GuoLin Li DongMei Li Chun Zhang ZhiHua Wang Department of Electronic Engineering Tsinghua University Beijing China

In order to decrease the communication bandwidth and save the transmitting power in the wireless endoscopy capsule, this paper presents a new near-lossless image compression algorithm suitable for hardware design based on the Bayer format image. This algorithm can provide low average compression rate (2.12 bits/pixel) with high image quality (larger than 53.11 dB) for endoscopic images. Especially, it has low complexity hardware overload and supports real-time compressing. In addition, the algorithm can provide lossless compression for the region of interest (ROI) and high quality compression for other regions. The ROI can be selected arbitrarily by varying ROI parameters.

关键词： Image coding Hardware Algorithm design and analysis Endoscopes Wireless sensor networks compression algorithms Low pass filters CMOS image sensors Sensor arrays Bandwidth

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Spatial and spectral decorrelation of lossless data compression for LANDSAT-TM imagery

Spatial and spectral decorrelation of lossless data compress...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Shouwen Tang Jinfei Wang Kaizhong Zhang Department of Computer Science Beijing Computer Institute Beijing China Department of Geography University of Windsor Windsor ONT Canada Department of Computer Science University of Western Ontario London ONT Canada

ISBN: (纸本)0780314972

Presents a spatial and spectral decorrelation scheme for lossless data compression of remotely sensed imagery. The statistical properties of Landsat-TM data are investigated. Measurements of the statistical information indicate that some bands have strong spectral correlation which can be used for interband prediction or spectral decorrelation; whereas other bands may be most suitable for spatial decorrelation within single band. Experiments show that data compression has been improved using both spatial and spectral nature of the remotely sensed data.< >

关键词： Decorrelation Data compression Satellites Remote sensing Image coding Least squares methods Computer science Multispectral imaging compression algorithms Entropy

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High performance compression of hyperspectral imagery with reduced search complexity in the compressed domain

High performance compression of hyperspectral imagery with r...

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Data compression Conference (DCC)

作者： F. Rizzo B. Carpentieri G. Motta J.A. Storer Dipartimento di Informatica e Applicazioni R. M. Capocelli Università degli Studi di Salerno SA Australia Computer Science Department Brandeis University Waltham MA USA

In previous work we considered LPVQ, a compression algorithm based on locally optimal partitioned vector quantization that can be used to compress hyperspectral images by applying partitioned VQ to the spectral signatures (e.g., to the 224 16-bit values of a NASA AVIRIS pixel) and then encoding error information with a threshold that can be varied from high quality lossy to near lossless to lossless (e.g., 50-to-1 lossy, 10-to-1 near lossless, or 3-to-1 lossless). An advantage of LPVQ is extremely fast decoding (table lookup followed by entropy decoding), but it is at the cost of more complex encoding. Here we present a new low complexity algorithm for hyperspectral image compression, called SLSQ, that employs linear prediction targeted at spectral correlation followed by entropy coding of the prediction error. We then consider how SLSQ can be combined with LPVQ in a scenario commonly arising in practice. In this scenario, a low-complexity lossless encoder on the remote acquisition platform compresses the data for transmission to a central computing facility, where it is processed and re-coded using LPVQ, so that the compressed data can be distributed to the final users at various quality levels. The VQ indices of the LPVQ form a lossy compressed image of only about 2% of the original size; this small image can be employed to greatly reduce the time for browsing and classification.

关键词： Image coding Hyperspectral imaging Decoding compression algorithms Vector quantization NASA Pixel Table lookup Entropy Costs

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Green Traffic compression in Wireless Sensor Networks

Green Traffic Compression in Wireless Sensor Networks

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IEEE Conference on Vehicular Technology (VTC)

作者： Kang-Hao Peng Kwang-Cheng Chen Shao-Lun Huang Shao-Chou Hung Xinhao Cheng Graduate Institute of Communication Engineering National Taiwan University Taipei Taiwan Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA China Research Laboratory IBM Research Shanghai China

ISBN: (纸本)9781479944811

Emerging multi-hop machine-to-machine (M2M) communications that likely support a large number of wireless devices create new challenges for spectrum scarcity and energy efficiency. In parallel to pursuing physical layer transmission efficiency, traffic compression to reduce required wireless transmissions suggests a new paradigm of wireless networks. Utilizing the natures of broadcasting and information collection in wireless sensor or machine networks, cognitive traffic compression can be facilitated by our proposed optimal fusion rules and topology compression algorithm. Therefore, only the necessary and connected sensors/machines in M2M networks are required to transmit, to achieve the desirable distortion of information collection (i.e. detection/estimation error). In other words, given the desirable distortion, the number of sensors to transmit, or equivalently the total energy consumption, serves our purpose of energy efficiency for end-to-end networking. Numerical results show successful compression of total network traffic to significantly enhance networking energy efficiency.

关键词： Wireless sensor networks Topology Network topology compression algorithms Robot sensing systems Wireless communication Fuses

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Data compression and decompression Integrated Circuit for AC Power Quality data

Data compression and decompression Integrated Circuit for AC...

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Annual IEEE Northeast Workshop on Circuits and Systems (NEWCAS)

作者： Marcos Hervé Cristiano Thiele Diógenes Machado Guilherme Wojichowski Cesar Crovato Sergio Bampi Altamiro Susin Embrasul Indústria Eletrônica LTDA Porto Alegre Brazil Electronic Engineering Department FEEVALE Hamburgo Brazil UFRGS PGMICRO - Informatics Institute Porto Alegre Brazil

ISBN: (纸本)9781509049929

This paper presents the integration of a Power Quality (PQ) data compression/decompression Application Specific Integrated Circuit (ASIC) into an AC power quality analyzer. The integration of the ASIC improves substantially the system data storage capabilities. The paper describes the compression algorithms implemented in dedicated CMOS circuitry. compression results obtained from real power line measurements are herein shown to prove the effectiveness of our compression/decompression ASIC. This chip has a die area of 15mm 2 , more than 400k 2-input logic gates equivalent, and 10 SRAM modules, all integrated into a 180nm digital CMOS technology. To the best of our knowledge this is the first lossy compression/decompression ASIC design for registering power quality trends over time, which is also compliant with the IEC 61000-4-30 standard accuracy requirements, fully tested and functional in a Class A system hardware PQ analyzer.

关键词： Power quality Voltage measurement Data compression compression algorithms Power measurement Application specific integrated circuits Harmonic analysis

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Tiled Image Container for Web Compatible Compound Image compression

Tiled Image Container for Web Compatible Compound Image Comp...

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International IEEE Conference on Signal-Image Technologies and Internet-Based System

作者： Ashok Mathew Kuruvilla Adobe Systems Inc.

Encoding images containing mixed content in web compatible formats like PNG, GIF and JPEG poses challenges in maintaining the quality along with good compression. In this paper, we describe a method for improving the compression of web compatible compound images while retaining high quality. The proposed method is based on the principle that the compression ratio of a given image depends upon both the image content and the compression algorithm used. Therefore, encoding various tiled regions in a given image with the algorithm appropriate to the content in the region improves the overall compression of the image. Further optimizations like sharing of indexed colors between the various tiles in the same image and removal of duplicate tiles improve the compression. This method would support both lossy and loss less compression. The resulting encoded data can be rendered by a web browser supporting CSS background-cropping or HTML5 canvas APIs.

关键词： Tiles Image coding Image color analysis Transform coding compression algorithms Compounds Image reconstruction

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compression of samplable sources

Compression of samplable sources

引用

Annual IEEE Conference on Computational Complexity

作者： L. Trevisan S. Vadhan D. Zuckerman Computer Science Division University of California Berkeley Berkeley CA USA Division of Engineering & Applied Sciences Harvard University Cambridge MA USA Department of Computer Science University of Technology Austin TX USA

We study the compression of polynomially samplable sources. In particular, we give efficient prefix-free compression and decompression algorithms for three classes of such sources (whose support is a subset of {0, l}/sup n/). 1) We show how to compress sources X samplable by logspace machines to expected length H(X) + O(1). Our next results concern flat sources whose support is in P. 2) If H(X) /spl les/ k = n - O(log n), we show how to compress to length k + /spl delta//spl middot/ (n - k) for any constant /spl delta/ > 0; in quasi-polynomial time we show how to compress to length k + O(polylog log (n - k)) even if k = n -polylog(n). 3) If the support of X is the witness set for a self-reducible NP relation, then we show how to compress to expected length H(X) + 4.

关键词： Polynomials Sampling methods Computer science Data compression Stochastic processes Distributed computing compression algorithms Information theory Random variables Entropy

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High frame rate medical quality video compression for tele-EEG

High frame rate medical quality video compression for tele-E...

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

作者： Laurent Lambert Syed Zahid Ahmed Khalil Hachicha Andrea Pinna Patrick Garda UPMC Univ Paris 06 Sorbonne Universités Paris France

ISBN: (纸本)9781457702198

More and more, exams require medical images as a tool to diagnose pathologies. Thus, the transfer and storage of the exam data becomes a critical issue. To address this issue, an image compression algorithm called Waaves has been developed and certified for medical imaging. Our work in this paper deals with a scenario of EEG exams where video of the patient is also recorded in order to correctly diagnose myoclonus pathologies. To achieve this goal, the video needs to be of high quality and at frame rate of at least 100 frames per second. This high data rate cannot be compressed on the fly by Waaves codec. In this paper, we present a novel codec based on the Waaves compression algorithm that fits the requirements of tele-video-EEG. We have used the characteristics of the input sequence and the analysis of the original codec, to improve the compression speed. The proposed video codec has shown a speed-up of around 3.4 times compared to the original algorithm. In addition, we have been able to improve the compression ratio while retaining necessary quality to identify myoclonus.

关键词： Codecs Discrete wavelet transforms Transform coding Image coding compression algorithms Bit rate Biomedical imaging

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