ITEM METADATA RECORD
Title: Wavelet-based image denoising using a Markov random field a priori model
Authors: Malfait, Maurits ×
Roose, Dirk #
Issue Date: Apr-1997
Publisher: Institute of Electrical and Electronics Engineers
Series Title: IEEE transactions on image processing vol:6 issue:4 pages:549-565
Abstract: This paper describes a new method for the suppression of noise in images via the wavelet transform, The method relies on two measures. The first is a classic measure of smoothness of the image and is based on an approximation of the local Holder exponent via the wavelet coefficients, The second, novel measure takes into account geometrical constraints, which are generally valid for natural images, The smoothness measure and the constraints are combined in a Bayesian probabilistic formulation, and are implemented as a Markov random field (MRF) image model, The manipulation of the wavelet coefficients is consequently based on the obtained probabilities, A comparison of quantitative and qualitative results for test images demonstrates the improved noise suppression performance with respect to previous wavelet-based image denoising methods.
ISSN: 1057-7149
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Numerical Analysis and Applied Mathematics Section
× corresponding author
# (joint) last author

Files in This Item:

There are no files associated with this item.

Request a copy

 




All items in Lirias are protected by copyright, with all rights reserved.

© Web of science