Comparison of robust M estimator, S estimator & MM estimator with Wiener based denoising filter for gray level image denoising with Gaussian noise

Authors

  • Mr. Pratyaksh A Maru Electronics and Communication Department, Dr. Jivraj Mehta Institute of Technology,Mogar, Anand, Gujarat, India.

Keywords:

Image Denoising, M-estimator, MM-estimator, Sestimator, Median filter, Wiener filter.

Abstract

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. In this paper we
evaluate the performance of MM-estimator, S-estimator, Mestimator, median filter and Wiener filter based image Denoising
filters for Gaussian noise. The Result shows that for Gaussian
noise wiener based filter gives good noise reduction compare to
other.

Published

2022-04-27

How to Cite

Mr. Pratyaksh A Maru. (2022). Comparison of robust M estimator, S estimator & MM estimator with Wiener based denoising filter for gray level image denoising with Gaussian noise. International Journal of Advance Engineering and Research Development (IJAERD), 2(13), -. Retrieved from http://ijaerd.com/index.php/IJAERD/article/view/5722