Denoising based on various segmentation methods Ms. Subhashini A.*, Dr. Victor S.P.** *M. Sc., MCA., M. Phil., Assistant Professor, PSG College of arts and Science, Avinashi Road, Civil Aerodrome Post, Coimbatore, Tamil Nadu **MCA, ME, Ph. D, Associate Professor, Computer Science, St. Xavier's College (Autonomous), Palayamkottai, Tirunelveli Online published on 24 October, 2019. Abstract Denoising is one of the important pre processing steps in image processing. The main aim of this paper is to denoise the image based on various segmentation methods. Some of the segmentation methods used in this paper is pixel based methods, edge based methods and region based methods. Thresholding, histogram based thresholding, k means clustering methods are explained under pixel based methods. Gradient based edge detection, laplacian based edge detection and canny edge detection are explained under edge detection methods. Region growing and region splitting & merging segmentation methods are explained under region based segmentation. We are concluding the paper with best method of segmentation for denoising. This paper gives advantages and disadvantages of various segmentation methods. Top Keywords Laplacian, gradient, canny edge detection, K means cluster, thresholding. Top |