Short Communication: Digital image restoration by Wiener filter in 2D case

Authors:
A. Khireddine;K. Benmahammed;W. Puech
Affiliations:
Electronic Department, Faculty of Sciences, University of Bejaia, Algeria and Electronic Department, Faculty of Sciences, University of Setif, Algeria;Electronic Department, Faculty of Sciences, University of Setif, Algeria;Lirmm Laboratory, University of Montpellier II, France
Venue:
Advances in Engineering Software
Year:
2007

Citing 1
Cited 3

Multivariate MIMO FIR inverses

IEEE Transactions on Image Processing

Vehicle image classification based on edge: features and distances comparison

ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part IV
Expert system applied for classifying self-compacting concrete surface finish

Advances in Engineering Software
Adaptive image restoration by a novel neuro-fuzzy approach using complex fuzzy sets

International Journal of Intelligent Information and Database Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

Modern digital technology has made it possible to manipulate multi-dimensional signals with systems that range from simple digital circuits to advanced parallel computers. The goal of this manipulation can be divided into three categories:*Image Processing image in-image out. *Image Analysis image in-measurements out. *Image Understanding image in-high-level description out. Further, we will restrict ourselves to two-dimensional (2D) image processing although most of the concepts and techniques that are to be described can be extended easily to three or more dimensions. The Wiener filter is a solution to the restoration problem based upon the hypothesized use of a linear filter and the minimum mean-square (or rms) error criterion. In the example given below the image a[m,n] was distorted by a bandpass filter and then white noise was added to achieve an SNR=30dB.