Non-subsampled contourlets and gray level co-occurrence matrix based images segmentation

Contourlet is a new geometric multiscale tool that is based on multiscale filters and directional filter banks. It not only inherits the multiscale characteristics of dimensionality-inseparable wavelets, but also has the flexible multi-directional characteristic by changing the directions of transform and sequences. In this paper, we developed a new non-subsampled contourlet transform (NSCT) and gray level co-occurrence matrix (GLCM) based image segmentation method. For the redundant and shift-invariant property of the NSCT, and the statistical texture features extracted by GLCM, the proposed method can present accurate segmentation result.