Removal of Additive White Noise Using an Adaptive Wiener Filter with Edge Retention


The Transactions of the Korea Information Processing Society (1994 ~ 2000), Vol. 6, No. 6, pp. 1693-1702, Jun. 1999
10.3745/KIPSTE.1999.6.6.1693,   PDF Download:

Abstract

This paper proposes the use of an adaptive Wiener filter for edge--preserving image filtering. Images are partitioned into a set of blocks of pixels which is divided into five subsets of blocks according to their edge contents and orientations. Each subset of blocks is used to define a covariance matrix, from which a Wiener filter is derived. Five covariance matrices and Wiener filters are thus obtained. An image--block classifier using the five sets of covariance matrices of the class is designed to classify each incoming block of pixels according to its edge content in the presence of noise. Experimental results are included to verify the usefulness of the proposed method.


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Cite this article
[IEEE Style]
D. J. Su, "Removal of Additive White Noise Using an Adaptive Wiener Filter with Edge Retention," The Transactions of the Korea Information Processing Society (1994 ~ 2000), vol. 6, no. 6, pp. 1693-1702, 1999. DOI: 10.3745/KIPSTE.1999.6.6.1693.

[ACM Style]
Do Jae Su. 1999. Removal of Additive White Noise Using an Adaptive Wiener Filter with Edge Retention. The Transactions of the Korea Information Processing Society (1994 ~ 2000), 6, 6, (1999), 1693-1702. DOI: 10.3745/KIPSTE.1999.6.6.1693.