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primary topic: Image SNR estimation using the autoregressive modeling

Image SNR estimation using the autoregressive modeling
type: AcademicArticle
type: Article
abstract: A number of techniques have been proposed during the last two decades for Signal-to-Noise Ratio (SNR) estimation in images. The majority of these techniques are based on the cross-correlation function of two images of the same area. However, the need for two images to estimate SNR value confines these techniques to non-stored images and thus limits their applications. In this paper the second order statistics of image corrupted by additive white noise are modeled by Autoregressive-model and the relationship between AR model and linear prediction is utilized in estimating the predictor coefficients. The predictor is then used to estimate the zero-offset autocorrelation value and accordingly obtain the power of the noise-free image. Unlike others, the proposed technique is based on single image and offers the required accuracy and robustness in estimating the SNR values.
date: 2010
status: peerReviewed
status: published
author list: authors
type: EPrint
type: ConferenceItemEPrint
is part of: repository

2010 International Conference on Intelligent and Advanced Systems, ICIAS 2010
type: Collection

N. Kamel
type: Person
given name: N.
family name: Kamel

S. Kafa
type: Person
given name: S.
family name: Kafa

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primary topic: Image SNR estimation using the autoregressive modeling