An Efficient Approach to De-noising Mammogram Images

Abstract: The noisy nature of digital mammograms and low contrast of doubtful areas which make medical images de-noising a challenging problem. In the field of image processing, different types of denoising algorithm are used to remove the unnecessary noise such as additive white Gaussian noise, salt and pepper noise, impulsive noise, as well used to smoothen the image. In the existing work, a novel gradient histogram preservation (GHP) algorithm was developed to improve the texture which exhibits the reduced quality in recognition of human image experiments. To remove the noise, Discrete Wavelet Transform (DWT) algorithm is used to eliminate the noisiness present in the medical image to preserve the texture structures. Proposed approach will efficiently calculate peak signal noise ratio (PSNR) parameters and make the enhanced image without noise and obtains the quality of image without any loss of data.

Keywords: Image Denoising, Discrete Wavelet Transform (DWT), Gaussian Filter, Mammogram image, Peak Signal-to-Noise Ratio.