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Proceedings Paper

Remote sensing images fusion based on block compressed sensing
Author(s): Sen-lin Yang; Guo-bin Wan; Bian-lian Zhang; Xin Chong
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Paper Abstract

A novel strategy for remote sensing images fusion is presented based on the block compressed sensing (BCS). Firstly, the multiwavelet transform (MWT) are employed for better sparse representation of remote sensing images. The sparse representations of block images are then compressive sampling by the BCS with an identical scrambled block hadamard operator. Further, the measurements are fused by a linear weighting rule in the compressive domain. And finally, the fused image is reconstructed by the gradient projection sparse reconstruction (GPSR) algorithm. Experiments result analyzes the selection of block dimension and sampling rating, as well as the convergence performance of the proposed method. The field test of remote sensing images fusion shows the validity of the proposed method.

Paper Details

Date Published: 30 August 2013
PDF: 8 pages
Proc. SPIE 8910, International Symposium on Photoelectronic Detection and Imaging 2013: Imaging Spectrometer Technologies and Applications, 891017 (30 August 2013); doi: 10.1117/12.2033808
Show Author Affiliations
Sen-lin Yang, Xi’an Univ. of Arts and Science (China)
Guo-bin Wan, Northwestern Polytechnical 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. 8910:
International Symposium on Photoelectronic Detection and Imaging 2013: Imaging Spectrometer Technologies and Applications
Lifu Zhang; Jianfeng Yang, Editor(s)

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