Anisotropic Nonstationary Image Estimation and Its Applications: Part I--Restoration of Noisy Images

TLDR: A new form of image estimator, which takes account of linear features, is derived using a signal equivalent formulation and shows that the method can improve the quality of noisy images even when the signal-to-noise ratio is very low.

Abstract: A new form of image estimator, which takes account of linear features, is derived using a signal equivalent formulation. The estimator is shown to be a nonstationary linear combination of three stationary estimators. The relation of the estimator to human visual physiology is discussed. A method for estimating the nonstationary control information is described and shown to be effective when the estimation is made from noisy data. A suboptimal approach which is computationally less demanding is presented and used in the restoration of a variety of images corrupted by additive white noise. The results show that the method can improve the quality of noisy images even when the signal-to-noise ratio is very low.

Full text

Linköping University Post Print
Anisotropic Non-Stationary Image Estimation
and its Applications: Part I. Restoration of
Noisy Images
Hans Knutsson, Roland Wilson and Gösta H. Granlund
N.B.: When citing this work, cite the original article.
©2009 IEEE. Personal use of this material is permitted. However, permission to
reprint/republish this material for advertising or promotional purposes or for creating new
collective works for resale or redistribution to servers or lists, or to reuse any copyrighted
component of this work in other works must be obtained from the IEEE.
Hans Knutsson, Roland Wilson and Gösta H. Granlund, Anisotropic Non-Stationary Image
Estimation and its Applications: Part I. Restoration of Noisy Images, 1983, IEEE
Transactions on Communications, (COM--31), 3, 388-397.
http://dx.doi.org/10.1109/TCOM.1983.1095832
Postprint available at: Linköping University Electronic Press
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-21582