Human visual system properties applied to image segmentation for image compression

Abstract

The authors describe a gray-level image segmentation method for use in segmentation-based image compression. The method consists of two steps: a variation of centroid-linkage region growing to perform the initial segmentation of the image, followed by nonlinear filtering to eliminate visually insignificant image segments. Both steps take advantage of human visual system properties to improve allocation of image segments. Subjective experiments have been conducted to determine the interactions and optimum balance between the steps. It is shown that the proposed two-step approach produces substantially better-quality segmented images than region growing used alone.