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For the remote sensing image fusion algorithm based on non-subsampled Contourlet transform (NSCT) calculation complexity and cannot extract details from source images effectively. So a new remote sensing image multi-feature fusion algorithm based on NSCT transform and compressive sensing is proposed. Firstly, luminance component V of multi-spectral image is extracted via HSV transform, and decompose the luminance component V and PAN image by NSCT; Then, Apply PCNN-based fusion rules to fusing low frequency sub-band, and the equivalent number is utilized as the linking strength; For the high frequency sub-band, a fusion rule based on the multi-feature in compressive sensing domain is presented; Finally, the fused images are obtained by inverse NSCT transform and inverse HSV transform, respectively. The experimental results show that the proposed fusion algorithm substantially outperforms the best-known remote sensing image fusion algorithms in terms of calculation complexity and the quality of the fused image, and has the better performance in visual effect and objective evaluation metrics

Remote sensing image multi-feature fusion based on NSCT transform and compressive sensing