DocumentCode :
1122399
Title :
A New Fuzzy Color Correlated Impulse Noise Reduction Method
Author :
Schulte, Stefan ; Morillas, Samuel ; Gregori, Valentín ; Kerre, Etienne E.
Author_Institution :
Dept. of Appl. Math. & Comput. Sci., Ghent Univ., Ghent, Belgium
Volume :
16
Issue :
10
fYear :
2007
Firstpage :
2565
Lastpage :
2575
Abstract :
A new impulse noise reduction method for color images is presented. Color images that are corrupted with impulse noise are generally filtered by applying a grayscale algorithm on each color component separately or using a vector-based approach where each pixel is considered as a single vector. The first approach causes artefacts especially on edge and texture pixels. Vector-based methods were successfully introduced to overcome this problem. Nevertheless, they tend to cluster the noise and to receive a lower noise reduction performance. In this paper, we discuss an alternative technique which gives a good noise reduction performance while much less artefacts are introduced. The main difference between the proposed method and other classical noise reduction methods is that the color information is taken into account to develop (1) a better impulse noise detection method and (2) a noise reduction method that filters only the corrupted pixels while preserving the color and the edge sharpness. Experimental results show that the proposed method provides a significant improvement on other existing filters.
Keywords :
fuzzy systems; image colour analysis; image denoising; impulse noise; color component; color images; fuzzy color correlated impulse noise reduction; grayscale algorithm; image edge; image texture pixels; lower noise reduction; vector-based approach; Adaptive filters; Color; Colored noise; Fuzzy systems; Gray-scale; Image edge detection; Information filtering; Information filters; Noise reduction; Statistics; Adaptive filtering; color image denoising; fuzzy filtering; fuzzy rule-based systems; Algorithms; Artifacts; Artificial Intelligence; Color; Colorimetry; Filtration; Fuzzy Logic; Image Enhancement; Image Interpretation, Computer-Assisted; Reproducibility of Results; Sensitivity and Specificity; Statistics as Topic;
fLanguage :
English
Journal_Title :
Image Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1057-7149
Type :
jour
DOI :
10.1109/TIP.2007.904960
Filename :
4303153
Link To Document :
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