Evaluation of different median filters for image processing tasks

Abstract

Impulsive noise is captured at the acquisition stage of digital image processing. It is an important step in the pre-processing process which is used to improve the image quality and make it more informative. There have been several proposed image-denoising algorithms, each with advantages and disadvantages. This work gives a thorough investigation of the median filter and its various variations for the reduction or elimination of impulsive noise in grey scale images. In terms of usefulness and comparative performance, Standard Median Filter, Adaptive Median Filter and Modified Median Filter are contrasted. On a set of pictures, thorough MATLAB-based simulations have been run to assess the performance of the current algorithms. Peak Signal to Noise Ratio was employed to compare performance in this case (PSNR). In terms of relative statistical performance, the Modified Median Filter (MMF) is the best.