Similarity based impulsive noise removal in color images

In this paper a novel approach to the problem of impulsive noise reduction in color images based on the nonparametric density estimation is presented. The basic idea behind the new image filtering technique is the maximization of the similarities between pixels in a predefined filtering window. The...

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Main Authors: Smolka, B., Plataniotis, K.N., Lukac, R., Venetsanopoulos, A.N.
Format: Conference Proceeding
Language:English
Subjects:
Color
Colored noise
Educational institutions
Filtering
Filters
Noise measurement
Noise reduction
Pixel
Strontium
Tail
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Plataniotis, K.N.
Lukac, R.
Venetsanopoulos, A.N.
description In this paper a novel approach to the problem of impulsive noise reduction in color images based on the nonparametric density estimation is presented. The basic idea behind the new image filtering technique is the maximization of the similarities between pixels in a predefined filtering window. The new method is faster than the standard vector median filter (VMF) and preserves better edges and fine image details. Simulation results show that the proposed method outperforms standard algorithms of the reduction of impulsive noise in color images.
doi_str_mv 10.1109/ICIP.2003.1246909
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source IEEE Xplore All Conference Series
subjects Color
Colored noise
Educational institutions
Filtering
Filters
Noise measurement
Noise reduction
Pixel
Strontium
Tail
title Similarity based impulsive noise removal in color images
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