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Journal of Electronic Imaging

Adaptive denoising and lossy compression of images in transform domain
Author(s): Karen O. Egiazarian; Jaakko T. Astola; Mika P. Helsingius; Pauli Kuosmanen
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Paper Abstract

A new algorithm for removing mixed noise from images based on combining an impulse removal operation with local adaptive filtering in transform domain is proposed in this paper. The key point is that the operation is designed so that it removes impulses while maintaining as much as possible of the frequency content of the original image. The second stage is an adaptive denoising operation based on local transform. The proposed algorithm works well in denoising images corrupted by a white (Gaussian, Laplacian, exponential) noise, impulsive noise, and their mixtures. Comparison of the new algorithm with known techniques for removing mixed noise from images shows the advantages of the new approach, both quantitatively and visually. In this paper we also apply transformbased denoising methods for removing blocking and ringing artifacts from decompressed block transform or wavelet coded images. The method is universal and applies to any compression method used.

Paper Details

Date Published: 1 July 1999
PDF: 13 pages
J. Electron. Imag. 8(3) doi: 10.1117/1.482673
Published in: Journal of Electronic Imaging Volume 8, Issue 3
Show Author Affiliations
Karen O. Egiazarian, Tampere Univ. of Technology (Finland)
Jaakko T. Astola, Tampere Univ. of Technology (Finland)
Mika P. Helsingius, Tampere Univ. of Technology (Finland)
Pauli Kuosmanen, Tampere Univ. of Technology (Finland)


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