OBJECTIVE QUALITY ASSESSMENT OF IMAGE ENHANCEMENT METHODS IN DIGITAL MAMMOGRAPHY-A COMPARATIVE STUDY

Mammography is the primary and most reliable technique for detection of breast cancer. Mammograms are examined for the presence of malignant masses and indirect signs of malignancy such as micro calcifications, architectural distortion and bilateral asymmetry. However, Mammograms are X-ray images taken with low radiation dosage which results in low contrast, noisy images. Also, malignancies in dense breast are difficult to detect due to opaque uniform background in mammograms. Hence, techniques for improving visual screening of mammograms are essential. Image enhancement techniques are used to improve the visual quality of the images. This paper presents the comparative study of different preprocessing techniques used for enhancement of mammograms in mini-MIAS data base. Performance of the image enhancement techniques is evaluated using objective image quality assessment techniques. They include simple statistical error metrics like PSNR and human visual system (HVS) feature based metrics such as SSIM, NCC, UIQI, and Discrete Entrop