Abstract
AbstractAn effective algorithm for automatic removal impulse noise from highly corrupted monochromatic images is proposed. The method consists of two steps. Outliers are first detected using local spatial relationships between image pixels. Then the detected noise pixels are replaced with the output of a rank-order filter over a local spatially connected area excluding the outliers, while noise-free pixels are left unaltered. Simulation results in test images show a superior performance of the proposed filtering algorithm comparing with conventional filters. The comparisons are made using mean square error, mean absolute error, and subjective human visual error criterion.KeywordsMean Square ErrorImpulse NoiseCentral PixelMean Absolute ErrorImpulsive NoiseThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
