Compressive sensing image fusion based on blended multi-resolution analysis

Focusing on the pixel level multi-source image fusion problem, the paper proposes an algorithm of compressive sensing image fusion based on the multi-resolution analysis. We present the method to decompose the images by nonsubsampled contourlet transform and wavelet successively, and fuse the images in the compressive domain. It means that the images can be sparsely represented by more than one basis functions. Since the nonsubsampled contourlet and wavelet basis functions have complementary advantages in the image multi-resolution analysis, and the signals are sparser after decomposed by two kinds of basis functions, the proposed algorithm has perceived advantages in comparison with CS image fusion in the wavelet domain which is widely reported by literatures. The simulations show that our method provides promising results.