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检索条件"主题词=Compression Algorithms"

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A novel B-mode ultrasound image compression method based on beam forming data

A novel B-mode ultrasound image compression method based on ...

引用

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

作者： Xiaojuan Li Guangshu Hu Shangkai Gao Department of Electrical Engineering Tsinghua University Beijing China

A novel coding method is presented for ultrasound image compression in teleultrasound system. The encoder chooses the video signals immediately after the ultrasonic beam forming as the object to be compressed other than the standard video images using in traditional methods. The compression algorithm is based on the 2-D discrete wavelet transform and arithmetic coding. Experiments on several images show satisfying results.

关键词： Ultrasonic imaging Image coding Discrete wavelet transforms Video compression Arithmetic compression algorithms Medical services Real time systems Data compression Discrete cosine transforms

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Symbol mapping and context filtering for lossless image compression

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IEEE International Conference on Image Processing

作者： Guang Deng Department of Electronic Engineering La Trobe University Bundoora VIC Australia

ISBN: (纸本)0818688211

Key building blocks of lossless image compression algorithms include adaptive prediction, context-based error feedback and adaptive entropy coding. This paper presents a new algorithm which includes two other building blocks-symbol mapping and context filtering. Experimental results show that the compression performance of the proposed algorithm is very close to that of CALIC and is better than that of LOGO and S+P. It is different from CALIC in the following aspects: (1) an adaptive median-FIR predictor, (2) a new error representation scheme using symbol mapping, (3) a different context calculation scheme for the prediction error, and (4) a new context filtering scheme.

关键词： Filtering Image coding Quantization Feedback Entropy coding Decoding Prediction algorithms Biomedical imaging compression algorithms Adaptive filters

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Decorrelation of IRS LISS-III data for lossless compression

Decorrelation of IRS LISS-III data for lossless compression

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： R.B. Inampudi M.I.V. Krishna Department of Computer Science & Engineering. Nagarjuna University Guntur Andhra Pradesh India Centre for Remote Sensing J.N.T. University Hyderabad India

The present paper analyses the scope of decorrelation as a tool for IRS data compression. Such a study was earlier carried out for Thematic Mapper. Now this study for 4 band data of IRS established the validity of spectral decorrelation for lossless compression. Most lossless compression algorithms in remote sensing applications use only spatial decorrelation. The authors concentrate mainly on spectral decorrelation. They first investigate the potential and limitations of spectral decorrelation methods for study of IRS data. Then spectral decorrelation usage is considered to achieve better compression ratio. The statistical properties of IRS data are also investigated. The image corresponds to agricultural area and forest areas. The statistical information indicates that some bands such as bands 1, 2 and 3 have strong spectral correlation while some other bands such as 1 and 4 have weak spectral correlation. This suggests that, by using spectral decorrelation, the authors may obtain better results for bands 1, 2 and 3. Experiments are carried out using this test IRS image. The image consists of four spectral channels and a spatial dimension of 1K/spl times/1K pixels. In this paper, lossless compression techniques proposed for Landsat TM multispectral images are applied for IRS data. These techniques provide methods to efficiently compute the optimal band combination and band ordering based on the statistical properties of multispectral image data. The authors' study on IRS LISS-III data showed that these techniques are capable of achieving higher compression ratios.

关键词： Decorrelation Image coding Remote sensing Entropy Multispectral imaging compression algorithms Pixel Satellites Digital images Computer science

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compression of echocardiographic data using the wavelet packet transform

Compression of echocardiographic data using the wavelet pack...

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Computers in Cardiology (CinC)

作者： X. Hang N. Greenberg J. Thomas Cleveland Clinic Foundation Ohio State Uinversity Cleveland USA

Archival of digital echocardiographic studies would be aided by efficient compression strategies that achieve a high compression ratio while maintaining high quality information for clinical interpretation. This paper presents the application of the wavelet packet transform in the compression of echocardiographic data (including still image and sequence data). We can achieve a good compromise between the retention of useful clinical information and providing a high compression ratio using the wavelet packet transform.

关键词： Wavelet packets Wavelet transforms Discrete wavelet transforms Image coding Discrete cosine transforms Image reconstruction compression algorithms Signal to noise ratio Image quality Chromium

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Advanced blocs classification for fast encoding in fractal-based gray-scale images compression

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IEEE International Conference on Image Processing

作者： K. Maalmi R. Benslimane Laboratoire de Transmission et de Tiraitament d 'Images Ecole Supérieure de Technologie de Fès

ISBN: (纸本)0818688211

Fractal-based images compression entails a computationally costly search for matching range and domain blocs. One way to remedy at this problem is to classify image blocs into categories and only search among domain blocs which are in the same category as the target range bloc. Since image blocs with a simple edge (blocs with a distinct edge running through them) are a very important portions of the perceptual information content in image, we propose in this paper a method to both identify and classify this kind of blocs according to their edge presentation. We refer to this method as forced classification (FC). This method is combined with other suitable methods of blocs classification available in the literature to allow a fast and efficient encoding of grey-scale images. The result is surprisingly good, the encoding time for 512/spl times/512 lena image is reduced by a factor of 37.52% than using only Yuval Fisher (1995) classification, while the loss of image quality is low.

关键词： Image coding Fractals Gray-scale Encoding Image quality Books Geometry compression algorithms Partitioning algorithms Mean square error methods

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A lossless image compression system using a binary arithmetic coder

A lossless image compression system using a binary arithmeti...

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International Conference on Signal Processing Proceedings (ICSP)

作者： Hua Ye Guang Deng J.C. Devlin Department of Electronic Engineering La Trobe University VIC Australia

In this paper we incorporate a binary arithmetic coder into a predictive lossless image compression scheme. Its idea arises from the observation that a binary arithmetic coder needs much less computation than a multi-symbol one and therefore should run faster. To map the prediction errors to binary symbols which are fed into the arithmetic coder, Rice code has been adopted because of the Laplacian distribution for prediction errors. Experiments show that the compression performance of this scheme is better than that of LOCO and S+P and is close to that of CALIC.

关键词： Image coding Arithmetic Entropy coding Laplace equations Prediction algorithms compression algorithms Probability Costs Redundancy Testing

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A simple lossless compression method-interval number method

A simple lossless compression method-interval number method

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

作者： Yong Xue M.M. Rees Xiangyu Sheng University Department of Clinical Radiology Bristol Royal Infirmary University of Bristol Bristol UK IESD De Montfort University Leicester UK

Lossless compression techniques-are essential in archival and communication of medical images. compression of medical images has been historically reversible or "lossless" limiting compression ratios to between 2:1 and 4:1. A new and simple lossless method-interval number-in the field of image compression in medical science is presented. The method is tested on several kinds of popular medical images. The general compression ratio is around 2:1. The best compression ratio can be 7.8:1 for X-ray images. It is shown that the interval number method is a very efficient and powerful method for medical image compression.

关键词： Image coding Biomedical imaging Medical diagnostic imaging Telemedicine Costs compression algorithms Predictive coding Predictive models Radiology Medical tests

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Mathematical methods for mapping image and data compression transforms to adaptive computing systems

Mathematical methods for mapping image and data compression ...

引用

OCEANS

作者： M.S. Schmalz E.X. Ritter F.H. Caimi Department of Computer and Information Science and Engineering University of Florida Gainesville FL USA Department of Electrical and Software Engineering Harbor Branch Oceanographic Institution Inc. Fort Pierce FL USA

The efficient computation of high-compression image transformations is the key to implementing video transmission in real-time applications that employ low-bandwidth communication links. In practice, such image compression applications could benefit from developments in adaptive computation, such as high-capacity field-programmable gate arrays (FPGAs) and reconfigurable SIMD meshes. It is noted that repetitive block structure in many compression algorithms tends to facilitate SIMD implementation. In contrast, the recursive data dependencies and variable partition size of pyramidally structured transforms such as wavelet-based compression may yield more effective processing with reconfigurable logic hardware such as FPGAs. In this paper, work-in-progress is presented that concerns mapping of image compression transforms to reconfigurable computing devices. The discussion begins with an overview of several compression algorithms in common use and their classification. The structure and function of two reconfigurable compression implementations (SIMD and FPGA) is described at a high level. The analysis emphasizes time and space complexity of each transformation and its associated implementations. Applications include exploitation of underwater acoustic channels for digital video telemetry.

关键词： Data compression Image coding Field programmable gate arrays Video compression compression algorithms Adaptive arrays Wavelet transforms Reconfigurable logic Hardware Underwater acoustics

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compression of image contours using combinatorial optimization

Compression of image contours using combinatorial optimizati...

引用

IEEE International Conference on Image Processing

作者： R. Nygaard J. Hakon Husoy D. Haugland Department of Electrical and Computer Engineering Hogskoleni Stavanger Stavanger Norway

compression of image contours is an important problem in many contexts. An example is object oriented video coding, where efficient encoding of shape information of arbitrarily shaped objects is a major problem. This paper presents a method for compressing contours by extracting representative points from the original curve. By formulating the point selection problem as a graph theory problem, known optimization theory can be applied in order to yield optimal compression with respect to a given error bound. The contour is reconstructed based on linear interpolation among the extracted curve points. The method presented guarantees a minimal distortion for a given number of retained curve points. Compared to many other compression methods, this method shows superior performance.

关键词： Image coding Data mining Image reconstruction Interpolation compression algorithms Video coding Encoding Shape Graph theory Data compression

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Image compression utilizing the DTOCS, topological raster patterns and delaunay triangulation

Image compression utilizing the DTOCS, topological raster pa...

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European Signal Processing Conference (EUSIPCO)

作者： Pekka J. Toivanen LUT-yliopisto Lappeenranta FI

In this paper, a new image compresion method is presented. It is based on the use of the Distance Transform on Curved Space (DTOCS), which calculates an integer approximation of the weighted pseudo-Euclidean distance transform along discrete 8-paths, and topological raster patterns to determine coordinates for control points. The decompression is based on triangulating among the control points using Delaunay triangulation. The obtained images are compared to previously published methods and to the JPEG DCT-based method. It is shown that the obtained results are of the same quality as JPEG results and exceed other DTOCS and Delaunay based methods. It is also shown experimentally that the time complexity of the compression method presented in this paper does not depend on the number of control points, i.e. the compression ratio. Because of this and the locality of the decompression scheme this method could well be used in applications where a rapid flashing image is made more accurate over time.

关键词： Image coding Transform coding Aerospace electronics Discrete cosine transforms Wavelet transforms compression algorithms

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