Author:
Hee-il Hahn
Affiliation:
Hankuk University of Foreign Studies, Korea, Republic of
Keyword(s):
Nonlinear denoising, robust statistics, robust estimation, maximum likelihood estimation, myriad filter, Cauchy distribution, amplitude-limited sample average filter, amplitude-limited myriad filter.
Related
Ontology
Subjects/Areas/Topics:
Image Processing
;
Informatics in Control, Automation and Robotics
;
Robotics and Automation
Abstract:
The statistics for the neighbor differences between the particular pixels and their neighbors are introduced. They are incorporated into the filter to enhance images contaminated by additive Gaussian and impulsive noise. The derived denoising method corresponds to the maximum likelihood estimator for the heavy-tailed Gaussian distribution. The error norm corresponding to our estimator from the robust statistics is equivalent to Huber’s minimax norm. This estimator is also optimal in the respect of maximizing the efficacy under the above noise environment. It is mixed with the myriad filter to propose an amplitude-limited myriad filter. In order to reduce visually grainy output due to impulsive noise, Impulse-like signal detection is introduced so that it can be processed in different manner from the remaining pixels. Our approaches effectively remove both Gaussian and impulsive noise, not blurring edges severely.