Abstract:

For traditional image fusion method results in loss of texture detail, a block compressed sensing image fusion algorithm in contourlet domain with a shift invariant and anti-aliasing ability called Contourlet_BCS was proposed. Contourlet_BCS introduced contourlet transform into the sparse representation step of compressed sensing since its remarkable feature of articulating the texture and edge information, meanwhile, the low-frequency coefficients fused by weighted rule of regional energy and high-frequency coefficients based on the weighted fusion rule by generalized Gaussian distribution model were also used. Finally, the high quality image can be reconstructed by smooth projection Landweber iteration method under the compressed sensing framework. Experimental results show that the image fused by Contourlet_BCS was better than the traditional method and the fusion image texture clear and had more abundant edge details.

Key words: block compressed sensing, Contourlet transform, generalized Gaussian distribution, weighted fusion