Compressive sensing image fusion based on blended multi-resolution analysis

Ying Tong; Leilei Liu; Meirong Zhao; Zilong Wei

doi:10.1117/12.2086338

6 March 2015 Compressive sensing image fusion based on blended multi-resolution analysis

Ying Tong, Leilei Liu, Meirong Zhao, Zilong Wei

Proceedings Volume 9446, Ninth International Symposium on Precision Engineering Measurement and Instrumentation; 94460G (2015) https://doi.org/10.1117/12.2086338
Event: International Symposium on Precision Engineering Measurement and Instrumentation, 2014, Changsha/Zhangjiajie, China

Abstract

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.

Citation Download Citation

Ying Tong, Leilei Liu, Meirong Zhao, and Zilong Wei "Compressive sensing image fusion based on blended multi-resolution analysis", Proc. SPIE 9446, Ninth International Symposium on Precision Engineering Measurement and Instrumentation, 94460G (6 March 2015); https://doi.org/10.1117/12.2086338

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