Mathematical Problems in Engineering
Volume 4 (1999), Issue 6, Pages 529-538
doi:10.1155/S1024123X98000957
Adaptive filters for color image processing
1University of Toronto, Toronto, ON M5S 3G4, Canada
2School of Computer Science, Ryerson Polytechnic University, ON M5B 2K3, Canada
3Digital Image Processing Laboratory, University of Toronto, ON M5S 3G4, Canada
Received 23 February 1998
Copyright © 1999 V. Papanikolaou et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
The color filters that are used to attenuate noise are usually optimized to perform extremely well when dealing with certain noise distributions. Unfortunately it is often the case that the noise corrupting the image is not known. It is thus beneficial to know a priori the type of noise corrupting the image in order to select the optimal filter. A method of extracting and characterizing the noise within a digital color image using the generalized Gaussian probability density function (pdf) (B.D. Jeffs and W.H. Pun, IEEE Transactions on Image Processing, 4(10), 1451–1456, 1995 and Proceedings of the Int. Conference on Image Processing, 465–468, 1996), is presented. In this paper simulation results are included to demonstrate the effectiveness of the proposed methodology.