Abstract
Mammography became the most efficient tool for early detection among breast cancer patients because it can detect cancer up to two years earlier than a mass can be shown. Pre-processing and post-processing of mammographic images involves high computational cost. Preprocessing is an essential element of any imaging modalities whose foremost aim is to execute such processes which can bring the image to that quality where it is suitable for further analysis and extraction of significant data. This paper talks about pre-processing which has great significance in mammographic image analysis due to poor quality of mammograms since they are captured at low dose of radiation while the high amount of radiation may jeopardize the patient's health. Many techniques have been used to enhance image quality, image smoothing and noise restoration. The experimental results conclude that the proposed Adaptive Weighted Frost filter is the best suitable choice for eliminating noise from mammographic images and performs better comparatively. The comparison of proposed technique with various existing techniques is performed both qualitatively and quantitatively. The experiments have demonstrated that the proposed technique provides better results as compare to existing techniques.