Visual Communications and Image Processing '96: 17-20 March, 1996, Orlando, Florida, Part 3 |
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Page 1082
... compression Marcia G. Ramos and Sheila S. Hemami School of Electrical Engineering , Cornell University , Ithaca , NY 14853 phone : ( 607 ) 255-8836 , fax : ( 607 ) 255-9072 e ... image compression [2727-102] G Ramos, S S Hemami, Cornell Univ.
... compression Marcia G. Ramos and Sheila S. Hemami School of Electrical Engineering , Cornell University , Ithaca , NY 14853 phone : ( 607 ) 255-8836 , fax : ( 607 ) 255-9072 e ... image compression [2727-102] G Ramos, S S Hemami, Cornell Univ.
Page 1360
... image compression has been paid great attention because of its potential of high compression ratio . In the previously published encoding techniques3,4 , an image is usually partioned into nonoverlapping blocks , and each block is ...
... image compression has been paid great attention because of its potential of high compression ratio . In the previously published encoding techniques3,4 , an image is usually partioned into nonoverlapping blocks , and each block is ...
Page 1394
... image compression is directly related to the metric used in the encoding process . In this paper , we introduce a perceptually meaningful distortion measure based on the human visual system's nonlinear response to luminance and the ...
... image compression is directly related to the metric used in the encoding process . In this paper , we introduce a perceptually meaningful distortion measure based on the human visual system's nonlinear response to luminance and the ...
Contents
Computer vision challenges and technologies for agile manufacturing 2727203 | 1036 |
Optimal lossy segmentation encoding scheme 272799 | 1050 |
Simultaneous parameter estimation and image segmentation for image sequence coding | 1062 |
Copyright | |
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applications approach background bilinear interpolation bit rate bit-rate block distortion block size boundary chain code channel check image cluster coder coding method color space components computation corresponding CPI algorithm decoder defined denote discrete cosine transform Dmar edge edge detection efficient equation error filter foreground fractal dimension fractal image frame frequency function Gaussian gradient IEEE Trans image coding image compression Image Processing image sequence input signal interpolation inverse iteration JPEG layer matching pursuit matrix Mojette transform motion compensation motion estimation motion parameters multichannel node noise number of levels object obtained optimal original image partition performance pixels polygon problem projections PSNR Q-factor quadpression quadtree quadtree decomposition quantization range block reconstruction regions resolution shown in figure solution spatial sub-images subband subblock technique threshold transform coding transform coefficient transmission vector vertex video coding wavelet