Image Segmentation Based on Non-Subsampled Contourlet and Normalized Cut

This paper describes an image segmentation algorithm based on Non-subsampled Contourlet (NSCT) and Normalized Cut (N-Cut). NSCT have the characteristics of multiresolutional, localized, multidirectional, and low redundant and anisotropic, so it is more effectively capture high dimensional singularity in an image. The segmentation is accomplishment by using normalize-cut rules after NSCT. The experiment results show the efficiency of image contour extraction, and avoid the problem of over-segmentation and under-segmentation phenomenon in N-Cut algorithm. In addition, because of less information in the low resolutions, the processing time is largely shortened, and then gets better segmentation results.