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Image SNR estimation using the autoregressive modeling

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2 Author(s)
Nidal Kamel ; Universiti Teknologi PETRONAS, EE-Dept, 31750, Tronoh, Perak, Malaysia ; Samir Kafa

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.

Published in:

Intelligent and Advanced Systems (ICIAS), 2010 International Conference on

Date of Conference:

15-17 June 2010