NONLINEAR AND MODEL-BASED IMAGE ANALYSIS

Adaptive denoising and lossy compression of images in transform domain

[+] Author Affiliations
Karen Egiazarian, Jaakko Astola, Mika Helsingius, Pauli Kuosmanen

Signal Processing Laboratory, Tampere University of Technology, Hermiankatu 12 C, P.O. Box 553, Tampere?33101, Finland

J. Electron. Imaging. 8(3), 233-245 (Jul 01, 1999). doi:10.1117/1.482673
History: Received Mar. 12, 1999; Revised Apr. 15, 1999; Accepted June 17, 1999
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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 transform-based 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. © 1999 SPIE and IS&T.

© 1999 SPIE and IS&T

Citation

Karen Egiazarian ; Jaakko Astola ; Mika Helsingius and Pauli Kuosmanen
"Adaptive denoising and lossy compression of images in transform domain", J. Electron. Imaging. 8(3), 233-245 (Jul 01, 1999). ; http://dx.doi.org/10.1117/1.482673


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