Compressive sensing (CS) has given us a new idea at data acquisition and signal processing. It has proposed some\nnovel solutions in many practical applications. Focusing on the pixel-level multi-source image-fusion problem in\nwireless sensor networks, the paper proposes an algorithm of CS image fusion based on multi-resolution analysis. We\npresent the method to decompose the images by nonsubsampled contourlet transform (NSCT) basis function and\nwavelet basis function successively and fuse the images in compressive domain. It means that the images can be sparsely\nrepresented by more than one basis function. We named this process as blended basis functions representation. Since\nthe NSCT and wavelet basis functions have complementary advantages in multi-resolution image analysis, and the signals\nare sparser after being decomposed by two kinds of basis functions, the proposed algorithm has perceived advantages in\ncomparison with CS image fusion in wavelet domain which is widely reported by literatures. The simulations show that\nour method provides promising results.
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