Slant Transform Image Coding
UNIVERSITY OF SOUTHERN CALIFORNIA LOS ANGELES ELECTRONIC SCIENCES LAB
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A slant transform matrix consisting of basis vectors which resemble typical lines of an image has been developed. A fast transform algorithm based on the matrix decomposition has also been presented. The transform has been proven to be superior, from the standpoint of image quality, to other transforms possessing fast computational algorithms. The statistical properties of the slant transform have been analyzed by introducing probability density and covariance models for the transform samples. The bandwidth reduction capability of the slant transform has been investigated by several test images. Two methods of achieving bandwidth reduction have been presented, namely, threshold and zonal coding. Studies have indicated that the average coding of a monochrome image can be reduced from 8 bitspixel to 1 bitpixel or 1.5 bitspixel for the threshold and zonal coding, respectively, without seriously degrading the image quality. Studies have also indicated that zonal coding has an extremely high noise immunity, and can be practically implemented. The average coding of a color image can be reduced from 24 bitspixel to 2 bitspixel by zonal coding while preserving good quality reconstruction.
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