Singular Value Decomposition For Image Coding
Harry C. Andrews · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1975
The numerical algorithm known as singular value decomposition [1] has been applied to image processing with interesting consequences [2 ]. Initially the algorithm was used to effect a pseudoinverse restoration [3 ] for better object estimation from degraded imagery. However the singular value decomposition (SVD) technique can also be effectively utilized in image compression problems when large compression ratios are desired. This Abstract refers to some experimental work developed at The Aerospace Corporation in which imagery has been compressed using SVD methods. Pictorial and computational results indicate that 8 bit imagery can be compressed to 2 bits with 0. 5% mean square error while the same imagery can be compressed to 1/2 bit with 1. 5% mean square error. These results will be presented along with various algorithms which make use of the SVD domain of an image for subsequent image compaction.