EFFICIENT EDGE EMPHASIZED MAMMOGRAM IMAGE ENHANCEMENT FOR DETECTION OF MICROCALCIFICATION

An efficient detection of microcalcification based on edge enhancement using discrete wavelet transform (DWT) is presented in this paper. The proposed method is implemented by separating the wavelet coefficients into weak and strong edge coefficients for effective detection of microcalcification. Identification of strong and weak edge locations corresponding to microcalcification is obtained by allowing the input image through appropriate filters before wavelet decomposition. Before reconstructing the output image, the strong and weak edge coefficients are modified based on the energy of the coefficients. The reconstructed image exhibits a better enhancement with the fine detail components of microcalcification than the original mammogram image. Standard Mias mammogram database images and clinical mammograms are used for testing and comparing subjective and objective measures of the mammogram images. A comparative study is made with the existing state-of-the-art edge enhancement and contrast enhancement methods and results are encouraging. The edge emphasizing ability of the proposed method is highly proficient in detection of microcalcification from the mammogram.