Color Image Segmentation Based on Hue-Saturation Similarity

Abstract

In this paper, we propose and develop a novel variational model based on hue-saturation similarity and fuzzy membership function for color image segmentation. The main contribution of the proposed model is that we determine different segments by using the similarity of hue and saturation information in hue, saturation, and value color space. We first provide specific definitions of the hue/saturation distance to describe hue-saturation similarity, then formulate a novel data fitting term with an adaptive weight coefficient by using hue-saturation similarity in the proposed energy functional. Two efficient iterative algorithms based on coordinate descent method and alternating direction method of multipliers have been proposed to solve the proposed optimization problem. Theoretically we study the existence of the solution of the proposed model and the convergence of the proposed coordinate descent algorithm. Numerical experimental results demonstrate that the segmentation performance of the proposed model is much better than that of other existing color image segmentation methods.