Skip Navigation

IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences 2008 E91-A(3):809-817; doi:10.1093/ietfec/e91-a.3.809
This Article
Right arrow Full Text (PDF)
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Request Permissions
Google Scholar
Right arrow Articles by NAKAMORI, S.
Right arrow Articles by LINARES-PÉREZ, J.
Right arrow Search for Related Content
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

Copyright © 2008 The Institute of Electronics, Information and Communication Engineers

Regular Section -- Papers -- Digital Signal Processing

Filtering in Generalized Signal-Dependent Noise Model Using Covariance Information

Seiichi NAKAMORI1, María J. GARCÍA-LIGERO2, Aurora HERMOSO-CARAZO2 and Josefa LINARES-PÉREZ2

1 The author is with the Faculty of Education, Kagoshima University, Kagoshima-shi, 890-0065 Japan. E-mail: nakamori{at}edu.kagoshima-u.ac.jp, 2 The authors are with the Department of Statistics, Granada University, 18071 Granada, Spain.


  Abstract

In this paper, we propose a recursive filtering algorithm to restore monochromatic images which are corrupted by general dependent additive noise. It is assumed that the equation which describes the image field is not available and a filtering algorithm is obtained using the information provided by the covariance functions of the signal, noise that affects the measurement equation, and the fourth-order moments of the signal. The proposed algorithm is obtained by an innovation approach which provides a simple derivation of the least mean-squared error linear estimators. The estimation of the grey level in each spatial coordinate is made taking into account the information provided by the grey levels located on the row of the pixel to be estimated. The proposed filtering algorithm is applied to restore images which are affected by general signal-dependent additive noise.

Key Words: film-grain noise, generalized signal-dependent noise, image filtering, covariance information

Manuscript received October 24, 2006. Manuscript revised October 25, 2007.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?




Disclaimer:
Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.