This paper introduces a new compression method for palettized images, which supports progressive refinement of the color information in contrast to the resolution refinement used in standard methods like interlaced GI...
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ISBN:
(纸本)0819437034
This paper introduces a new compression method for palettized images, which supports progressive refinement of the color information in contrast to the resolution refinement used in standard methods like interlaced GIF. Such, fine image details can be recognized after decoding only a small part of the compressed imagedata. Achieved compression ratios are comparable to those of interlaced GIF or PKG. The method combines color map sorting with bitplane by bitplane prediction and Golomb coding of the pixel held.
This paper mainly describes the high quality imagecompression system using modified motion vector detection for the multi-directional stereo imaging system. The data rate of high resolution imaging system would excee...
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ISBN:
(纸本)9780780395091
This paper mainly describes the high quality imagecompression system using modified motion vector detection for the multi-directional stereo imaging system. The data rate of high resolution imaging system would exceed more than several Gbits/sec, and the multi-directional imaging system furthermore increases the above data rate. Accordingly, the large grade of datacompression should be indispensable in the transmission of high spatial multi-stereo imaging data. The paper proposes the new compression method based on the modified motion vector detection and applying JPEG2000((1)) and JPEG-LS(1,2) compression methods. The paper reveals the effectiveness of the averaging of the motion vector between the successive multi-stereo imaging data. As the results, the paper shows the proposed method is superior to ordinary JPEG2000 or JPEG-LS in the quality of signal to noise ratio, and can reduce the data rate to less value than conventional compression method.
We propose a novel method for simultaneous speckle reduction and datacompression based on shrinking, quantizing and coding the wavelet packet coefficients of the logarithmically transformed image. A fast algorithm is...
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ISBN:
(纸本)0819418447
We propose a novel method for simultaneous speckle reduction and datacompression based on shrinking, quantizing and coding the wavelet packet coefficients of the logarithmically transformed image. A fast algorithm is used to find the best wavelet packet basis in the rate- distortion sense from the entire library of admissible wavelet packet bases. Soft-thresholding in wavelet domain can significantly suppress the speckles of the synthetic aperture radar (SAR) images while maintaining bright reflections for subsequent detection and recognition. Optimal bit allocation, quantization and entropy coding achieve the goal of compression while maintaining the fidelity of the SAR image.
Many multimedia applications deal with image progressive transmission in order to reduce channel bandwidth and to allow for interactivity between users and service providers. In this framework, the paper presents a no...
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ISBN:
(纸本)0819429880
Many multimedia applications deal with image progressive transmission in order to reduce channel bandwidth and to allow for interactivity between users and service providers. In this framework, the paper presents a novel two-source coding scheme where thumbnail data are interpolated by fractal zooming to obtain higher resolution images;the relevant residual information is then coded by vector quantizing the wavelet decomposition coefficients. Performance of this novel scheme is evaluated on a variety of pictures, confirming its validity both in quantitative (MSE) and qualitative terms (absence of block distortion).
An update of the development status of the CWIC on-board image compressor project is given. For the convenience of the reader, the features of CWIC are recollected: Riavelet-based, high-speed, high resolution, constan...
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ISBN:
(纸本)0819437603
An update of the development status of the CWIC on-board image compressor project is given. For the convenience of the reader, the features of CWIC are recollected: Riavelet-based, high-speed, high resolution, constant-rate imagecompression using space-qualifiable hardware. The compression efficiency of CWIC has been reported earlier but is supplemented with a JPEG comparison presently. The precise real-time performance of CWIC has been obtained from netlist simulation. The CWIC architecture is shown with two interface options: either a parallel or a SpaceWire serial interface. The status of the demonstrator is reported, and the existing filter and coder boards are depicted.
To explore the latent information of Human Knowledge, the analysis for Knowledge Bases (KBs) (e.g. WordNet, Freebase) is essential. Some previous KB element embedding frameworks are used for KBs structure analysis and...
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ISBN:
(纸本)9781509061839
To explore the latent information of Human Knowledge, the analysis for Knowledge Bases (KBs) (e.g. WordNet, Freebase) is essential. Some previous KB element embedding frameworks are used for KBs structure analysis and completion. These embedding frameworks use low-dimensional vector space representation for large scale of entities and relations in KB. Based on that, the vector space representation of entities and relations which are not contained by KB can be measured. The embedding idea is reasonable, while the current embedding methods have some issues to get proper embeddings for KB elements. The embedding methods use entity-relation-entity triplet, contained by most of current KB, as training data to output the embedding representation of entities and relations. To measure the truth of one triplet (The knowledge represented by triplet is true or false), some current embedding methods such as Structured Embedding (SE) project entity vectors into subspace, the meaning of such subspace is not clear for knowledge reasoning. Some other embedding methods such as TransE use simple linear vector transform to represent relation (such as vector add or minus), which can't deal with the multiple relations match or multiple entities match problem. For example, there are multiple relations between two entities, or there are multiple entities have same relation with one entity. Insipred by previous KB element structured embedding methods, we propose a new method, Bipartite Graph Network Structured Embedding (BGNSE). BGNSE combines the current KB embedding methods with bipartite graph network model, which is widely used in many fields including image data compression, collaborative filtering. BGNSE embeds each entity-relation-entity KB triplet into a bipartite graph network structure model, represents each entity by one bipartite graph layer, represents relation by link weights matrix of bipartite graph network. Based on bipartite graph model, our proposed method has following
This article presents a fuzzy system and a neural network that adaptively classify subimages according to their image activity distribution. Subimages in each class are encoded with different bit allocation matrices d...
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