Implementation and Comparison of the Spatial Denoising Filter for Impulse Noise on MIAS Dataset - Ramya, A; Murugan, D; Muthulakshmi, G (International Journal of Computer Sciences and Engineering, 2025)
Image preprocessing is the important phase in digital image processing domain to analyze the undesirable signal present in an image and removal of the same. For any further processing of an image, noise removal is mandatory to get the desired resultant. Before applying any noise removal algorithm to an image, it is obligatory to understand what kind of noise that exactly presents in an image. In this paper, we have handled the impulse noise presence in mammogram image and various spatial based median filters are applied to it. Initially, to confirm the impulse noise presence, the sub-window of an image is subjected to undergo the detection process, where the impulse noise pixels are identified. Secondly, for the detected noise window the traditional median filter is applied. This process does not affect the image quality and produces the noise-free enhanced image. Finally, we have experimented and compared the five different median based denoising algorithms, each one has different detection framework and found the best denoising algorithm for impulse noise removal with the help of qualitative and quantitative metrics