Chapter 1 - Introduction

Abstract

Since the early 1970s, block transforms with real basis functions, particularly the discrete cosine transform (DCT), have been studied extensively for transform coding applications. The availability of simple fast transform algorithms and good signal coding performance made the DCT the standard signal decomposition technique, particularly for image and video. The international standard image–video coding algorithms, i.e., CCITT H.261, JPEG, and MPEG, employ DCT-based transform coding. The recognition that multi-resolution signal decomposition is a by-product of multirate subband, filter banks generated significant interest in the design of better performing filter banks for visual signal processing applications. The wavelet transform with a capability for variable time-frequency resolution has been promoted as an elegant multi-resolution signal processing tool that is strongly linked to subband decomposition. This linkage stimulated additional interest in subband filter banks, because they serve as the only vehicle for fast orthonormal wavelet transform algorithms and wavelet transform basis design. By visual signal processing and coding applications, the properties of the human visual system (HVS) are examined and incorporated in the signal decomposition step. It has been reported that the HVS inherently performs multiresolution signal processing that triggered significant interest in multiresolution signal decomposition and its mathematical foundations in multirate signal processing theory. The multiresolution signal analysis concept has applications in visual signal processing and visual communications. Progressive improvement of the signal quality in visual applications, from coarser to finer resolution, has many uses in computer vision, visual communications, and related fields.