Application of H∞ optimization techniques in image & signal processing

Abstract

Image processing has been receiving extensive attention in recent years because of its potential applications to a number of fields. Video, Audio, and Images produce vast amount of data which requires a tremendous amount of memory for its storage, and could not possibly be faithfully transmitted due to channel bandwidth limitation. The only solution is to compress the data involved. Six new algorithms are proposed for the data compression problem. Comparisons are made with an implemented Discrete Cosine Transform (DCT)-based compression method. One of the algorithms is modified and applied to a speech signal. The performance and evaluation of these new algorithm are addressed based on fidelity criteria, and implemented examples are given.