Loading [a11y]/accessibility-menu.js
Removal of High-Density Salt-and-Pepper Noise in Images With an Iterative Adaptive Fuzzy Filter Using Alpha-Trimmed Mean | IEEE Journals & Magazine | IEEE Xplore

Removal of High-Density Salt-and-Pepper Noise in Images With an Iterative Adaptive Fuzzy Filter Using Alpha-Trimmed Mean


Abstract:

Suppression of impulse noise in images is an important problem in image processing. In this paper, we propose a novel adaptive iterative fuzzy filter for denoising images...Show More

Abstract:

Suppression of impulse noise in images is an important problem in image processing. In this paper, we propose a novel adaptive iterative fuzzy filter for denoising images corrupted by impulse noise. It operates in two stages-detection of noisy pixels with an adaptive fuzzy detector followed by denoising using a weighted mean filter on the “good” pixels in the filter window. Experimental results demonstrate the algorithm to be superior to state-of-the-art filters. The filter is also shown to be robust to very high levels of noise, retrieving meaningful detail at noise levels as high as 97%.
Published in: IEEE Transactions on Fuzzy Systems ( Volume: 22, Issue: 5, October 2014)
Page(s): 1352 - 1358
Date of Publication: 21 October 2013

ISSN Information:


Contact IEEE to Subscribe

References

References is not available for this document.