A Comparative Analysis on Various Noise Reduction Techniques Tested for Medical Images

Noise removing in the medical image is still a challenging task in the research field especially for the imaging devices like mammogram and ultra-sound. Even though advance scanning technology has been invented, these conventional devices play a vital role in scanning the mammogram breast cancer and fetus images. During the image acquisition itself, these images will get corrupted by the physical interference which appears as a noise in an image and affects its visual quality. In this paper we have applied the various traditional and conventional mean based noise removal techniques for the impulse noise corrupted mammogram breast image and standard benchmark. From this comparative analysis we have found that alpha-trimmed mean filters gives the better result than the other filters in terms of PSNR, SSIM and visual quality.