Brain Tumor Image Edge & Watershed Segmentation and Denoising Using DWT

Image segmentation is a mechanism used to divide an image into multiple segments. It will make image smooth and easy to evaluate. Segmentation process also helps to find region of interest in a particular image. The main goal is to make image more simple and meaningful. Existing segmentation techniques can’t satisfy all type of images. The scope of the paper is to evaluate the brain tumor image quality edge & watershed segmentation technique by DWT, implemented using MATLAB and simulation carried out on using jpeg image format. To identify tumor from the brain of effected area using edge watershed segmentation then applied to DWT to get good quality image. This paper introduces an efficient detection of brain tumor from cerebral MRI images. The methodology consists of three steps: edge segmentation, watershed segmentation and denoising by DWT. The Wavelet Transform applied in the segmentation process to decompose MRI image, to find the quality of an image by calculating PSNR and MSE. Some of experimental results on brain image show the feasibility and the performance of the proposed approach.