Spatio-Chromatic Image Enhancement Based on a Model of Human Visual Information Processing

Abstract

A technique for color image enhancement based on a model of the human visual system (HVS) is presented. A color image represented by RGB is first transformed into a color space based on the HVS cone response characteristics. Subsequently, chromatic correlation reduction and energy compression is realized by using a multispectral Karhunen-Loéve transform (KLT) of the cone responses. This yields a color opponent space related to the HVS characteristics. Spatial energy distribution is highly skewed; the chromatic channels contain significantly less relative energy than in standard opponent spaces such as YUV. A constant transform, which closely approximates the input-dependent KLT, has been found. In spite of the little spatial energy in the chromatic channels, chromatic edge enhancement in this space does add significantly to the perception of image detail and enhances its chromatic fidelity, as compared with standard edge enhancement of only the luminance channel. Chromatic edge enhancement is also less sensitive to noise than achromatic edge enhancement. Owing to the simplicity of the transform and enhancement processes, they can be employed for processing real-time video signals. © 1998 Academic Press.