Segmentation of image with DT-CWT and NLM filtering using fuzzy c-means clustering

A novel approach for image segmentation is proposed in which, the output of Image Resolution Enhancement using Dual-Tree Complex Wavelet Transform is given as input to the Fuzzy C-Means Clustering technique. The FCM calculates fuzziness for the belongingness of each image pixels i.e., FCM was used to generate an initial contour curve which removes leaking at the boundary during the curve propagation. Based on FCM the edge indicator function was defined. The edge indicator function of a image was performed to extract the boundaries of objects on the basis of the pre segmentation. Fuzzy clustering methods quantitatively determine the affinities of different objects with mathematical methods, described by a member function, to divide types objectively. Therefore, the proposed method is computationally efficient.