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Proceedings Paper

Compressive sensing image fusion based on blended multi-resolution analysis
Author(s): Ying Tong; Leilei Liu; Meirong Zhao; Zilong Wei
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Paper 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.

Paper Details

Date Published: 6 March 2015
PDF: 6 pages
Proc. SPIE 9446, Ninth International Symposium on Precision Engineering Measurement and Instrumentation, 94460G (6 March 2015); doi: 10.1117/12.2086338
Show Author Affiliations
Ying Tong, Tianjin Univ. (China)
Tianjin Normal Univ. (China)
Leilei Liu, Tianjin Univ. (China)
Meirong Zhao, Tianjin Univ. (China)
Zilong Wei, Tianjin Univ. (China)


Published in SPIE Proceedings Vol. 9446:
Ninth International Symposium on Precision Engineering Measurement and Instrumentation
Junning Cui; Jiubin Tan; Xianfang Wen, Editor(s)

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