Image modeling and restoration: A new approach
type: Item
instance of: scholarly article
title: Image modeling and restoration: A new approach
zbMATH Open document ID: 0677.68123
DOI: 10.1007/BF01599919
published in: Circuits, Systems, and Signal Processing
publication date: 1988-01-01T00:00:00Z
review text: Many image restoration methods proposed in the literature are based on the assumption that the image spatial correlation can be approximated by an autocorrelation function which is to be obtained from the original image. If a noise-free image is not available, the autocorrelation function must be estimated. The main drawbacks of these methods are the increased complexity and the high computational cost. The authors propose here a restoration procedure which does not require a priori knowledge of the autocorrelation function or the use of identification-estimation algorithms. The basic hypothesis is that the image can be modeled as an ensemble of two-dimensional differentiable surfaces. This idea is embedded in a bidimensional Kalman filtering approach.
Mathematics Subject Classification ID: 68U99
zbMATH DE Number: 4110187
zbMATH Keywords: image modeling
zbMATH Keywords: Kalman filtering
zbMATH Keywords: image restoration
author: A. Germani
author: Leopoldo Jetto
reviewed by: R. Andonie
MaRDI profile type: Publication
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full work available at URL: https://doi.org/10.1007/bf01599919
OpenAlex ID: W4248106827
description: scientific article; zbMATH DE number 4110187