Comparative Analysis of Noise Reduction Filters for the Quality Enhancement of Mammography Images

Enhancement of the mammography image quality is an important step for precise diagnosis and early breast cancer detection. A comparison of different noise reduction filters used on mammography images is presented in this paper. We evaluate the denoising performance of filters such as Gaussian, Median, and Adaptive median filters. In addition to qualitative assessments by qualified radiologists, the study is predicated on quantitative measures like Mean Squared Error (MSE), Discrete entropy, AMBE, (Absolute Average Brightness Error), and Peak Signal-to-Noise Ratio (PSNR). This thorough assessment offers insightful guidance on how to choose the best noise reduction methods to improve the quality of mammography images, which will ultimately contribute to more accurate breast cancer screening and diagnosis.