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Proceedings Paper

Images fusion based on block compressed sensing and multiwavelet transform
Author(s): Sen-lin Yang; Guo-bin Wan; Jing-huai Gao; Bian-lian Zhang; Xin Chong
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Paper Abstract

A novel strategy for images fusion is presented based on the block compressed sensing (BCS) and multiwavelet transform (MWT). Since the BCS requires small memory requirement and enables fast computation, the images with large amounts of data can be compressively sampled by the BCS. Secondly, taking full advantages of multiwavelet such as symmetry, orthogonality, short support, and a higher number of vanishing moments, the compressive measurements of images can be better represented by the MWT. Moreover, the compressive measurements are fused based on the coherence of MWT decomposition coefficients. And finally, the fused image is reconstructed by the minimization of total variance method, and an overlapped blocking technique is proposed to eliminate the block effects. Experiments result shows the validity of the proposed method. Simultaneously, results also indicate that the compressive fusion can produce better results than conventional fusion techniques such as the principle component analysis method, Laplacian pyramid-based method, and wavelet transform method.

Paper Details

Date Published: 20 August 2013
PDF: 9 pages
Proc. SPIE 8913, International Symposium on Photoelectronic Detection and Imaging 2013: Optical Storage and Display Technology, 89130R (20 August 2013); doi: 10.1117/12.2033237
Show Author Affiliations
Sen-lin Yang, Xi’an Univ. of Arts and Science (China)
Guo-bin Wan, Northwestern Polytechnical Univ. (China)
Jing-huai Gao, Xi’an Jiaotong Univ. (China)
Bian-lian Zhang, Xi’an Univ. of Arts and Science (China)
Xin Chong, Emerson Network Power Ltd. (China)


Published in SPIE Proceedings Vol. 8913:
International Symposium on Photoelectronic Detection and Imaging 2013: Optical Storage and Display Technology
Changsheng Xie; Yikai Su; Liangcai Cao, Editor(s)

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