Remote sensing images fusion based on block compressed sensing

Sen-lin Yang; Guo-bin Wan; Bian-lian Zhang; Xin Chong

doi:10.1117/12.2033808

30 August 2013 Remote sensing images fusion based on block compressed sensing

Sen-lin Yang, Guo-bin Wan, Bian-lian Zhang, Xin Chong

Proceedings Volume 8910, International Symposium on Photoelectronic Detection and Imaging 2013: Imaging Spectrometer Technologies and Applications; 891017 (2013) https://doi.org/10.1117/12.2033808
Event: ISPDI 2013 - Fifth International Symposium on Photoelectronic Detection and Imaging, 2013, Beijing, China

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.

Citation Download Citation

Sen-lin Yang, Guo-bin Wan, Bian-lian Zhang, and Xin Chong "Remote sensing images fusion based on block compressed sensing", Proc. SPIE 8910, International Symposium on Photoelectronic Detection and Imaging 2013: Imaging Spectrometer Technologies and Applications, 891017 (30 August 2013); https://doi.org/10.1117/12.2033808

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