Singular Value Decomposition (SVD) Image Coding

The numerical techniques of transform image coding are well known in the image bandwidth compression literature. This concise paper presents a new transform method in which the singular values and singular vectors of an image are computed and transmitted instead of transform coefficients. The singular value decomposition (SVD) method is known to be the deterministically optimal transform for energy compaction [2]. A systems implementation is hypothesized, and a variety of coding strategies is developed. Statistical properties of the SVD are discussed and a self adaptive set of experimental results is presented, Imagery compressed to 1, 1.5, and 2.5 bits per pixel with less than 1.6, 1, and 1/3 percent, respective mean-square error is displayed. Finally, additional image coding scenarios are postulated for further consideration.