A novel remote sensing image fusion scheme based on NSCT and Compressed Sensing

<p> In this letter, we propose a novel remote sensing image fusion method based on the non-subsampled contourlet transform and the compressed sensing (CS) theory.[2][3] Method First, the IHS transformation of the multispectral images is conducted to extract the I component. Secondly, the panchromatic image and the component intensity of the multispectral image are decomposed by NSCT. Then the NSCT coefficients of high and low frequency subbands are fused by different rules, respectively. For the high frequency subbands, the absolute maximum selection rule is used to integrate high-pass subbands; while the adaptive regional energy weighting rule is proposed to fuse low-pass subbands. The sparse coefficients are fused before being measured by Gaussian matrix. The fused image is accurately reconstructed by Compressive Sampling Matched Pursuit algorithm (CoSaMP). Some experiments are taken to investigate the performance of our proposed method, and the results prove its superiority to the counterparts. &copy; 2017 SPIE.