(untitled) (International Journal of Advanced Research in Computer Science, 2017)
Mammograms are X-ray images of the breast. Digital mammogram is to detect abnormalities in the breast, which may require monitoring or treatment. Early detection is the most appropriate treatment to reduce breast cancer mortality. Mammogram images are poor in quality due to low dose radiation, because higher dose may destroy patient’s health. Mammogram images affected by noise can degrade the quality of an image which leads to wrong diagnosis by a radiologist. The goal of pre-processing is to enhance the quality by removing the noise and to preserve the details in an image which is suitable for further analysis. This paper proposes a novel idea to de-noise the image by introducing a hybrid statistical filter which is a combination of maximum, deviation about mean and median. Performance Evaluation is done based on the metrics Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR). The proposed filter yields better results compared to existing filters. Keywords: Mammogram; Pre-processing; Noise; Maximum; Median; Variance