Comparison of Robust MM Estimator and Robust M Estimator Based Denoising Filters for Gray Level Image Denoising

In any image processing system denoising of images is an important step. The images can be corrupted by different noises with different levels. There are three types of noises available: impulse, Gaussian and Speckle noises with mixture of them. Many algorithms are proposed to remove salt & pepper (impulse) noise as well as Gaussian noise. The Robust statistics based filter is also proposed to remove either impulse or Gaussian noise using Lorentian rho function based robust M estimator. However, there is still a need to find a most efficient filter for image denoising, which can be effective for salt & pepper noise with different noise levels. In this paper we evaluate the performance of MM-estimator and M-estimator based image denoising filters for salt & pepper noise only. The results show very good impulse noise removal by MM estimator compared to M-estimator.