The Morphological Component Analysis and Its Application to Color-gray Image Fusion ⋆

This paper focuses on a new color-gray image fusion algorithm based on Morphological Component Analysis (MCA) which is a novel decomposition (separation) method based on sparse representation of signals and images. The interest of the newly proposed fusion algorithm is the ability of preserving textural information. In our fusion scheme, color original images are transformed into gray-scale images firstly. Secondly, we discompose the gray-scale images into smooth parts and textural parts, and thirdly fuse them respectively; fourthly, gray-scale fused image is obtained by adding the two fused parts. Finally, the color fused images are achieved based on the gray-scale fused image. We tested the algorithm in medical and biological images, and experimental results justify the superiority of the fusion algorithm.