Support vector machine based on nonsubsampled contourlet transform for fusing multi-focus images

The nonsubsampled Contourlet transform (NSCT) provides a shift-invariant directional multiresolution image representation, which leads to a NSCT with better frequency selectivity and regularity. A new approach is improved to fuse multi-focus images with support vector machine(SVM) based on NSCT. The features from the NSCT coefficients are used and SVMs are trained to determine whether coefficients from the source image with the best focus should be used. The kernels of SVMs are improved by using region variance and region energy. The fused NSCT coefficients are used to reconstruct fused image. Experimental results show that the proposed method fuses multi-focus images effectively and accurately.