Color Image Compression: Early Vision and the Multiresolution Representations

Abstract

AbstractThe efficiency of an image compression technique relies on the capability of finding sparse M-terms for best approximation with reduced visually significant quality loss. By ”visually significant” it is meant the information to which human observer can perceive. The Human Visual System (HVS) is generally sensitive to the contrast, color, spatial frequency...etc. This paper is concerned with the compression of color images where the psycho-visual representation is an important strategy to define the best M-term approximation technique. Digital color images are usually stored using the RGB space, television broadcast uses YUV (YIQ) space while the psycho-visual representation relies on 3 components: one for the luminance and two for the chrominance. In this paper, an analysis of the wavelet and contourlet representation of the color image both in RGB and YUV spaces is performed. A approximation technique is performed in order to investigate the performance of image compression technique using one of those transforms.KeywordsColor ImageDiscrete Cosine TransformColor SpaceDiscrete Wavelet TransformImage CompressionThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.