Medical Image Fusion in NSCT Domain Combining with Compressive Sensing

In recent years, with the development of compressive sensing (CS) theory, it has been widely applied to each field including image fusion, and obtained better fusion effect. And CS can reduce dimensions and the amount of data characteristics as well as the large amount and high computation complex. Therefore, this paper proposes a novel medical image fusion method based on compressive sensing theory in non-subsampled contourlet transform (NSCT) domain. First, NSCT transform is applied to the source images, and the coefficients in low frequency subband are fused by mean rules. For high frequency subband, CS is applied and the coefficients are fused by neighborhood-energy-MAX (NEMAX) rule, then inverse CS is used to get fused coefficients. Finally, inverse NSCT is applied to get the reconstructed image. The experimental results show that the fusion algorithm proposed in this paper is superior to fusion method based on WT-MAX and CSMAX、CS-MEAN.