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Image signal-to-noise ratio and noise variance estimation using autoregressive model

Kamel , Nidal and Sim, K.S. (2004) Image signal-to-noise ratio and noise variance estimation using autoregressive model. [Citation Index Journal]

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Official URL: http://onlinelibrary.wiley.com/journal/10.1002/(IS...

Abstract

During the last three decades, several techniques have been proposed for signal-to-noise ratio (SNR) and noise variance estimation in images, with different degrees of success. Recently, a novel technique based on the statistical autoregressive model (AR) was developed and proposed as a solution to SNR estimation in scanning electron microscope (SEM) image. In this paper, the efficiency of the developed technique with different imaging systems is proven and presented as an optimum solution to image noise variance and SNR estimation problems. Simulation results are carried out with images like Lena, remote sensing, and SEM. The two image parameters, SNR and noise variance, are estimated using different techniques and are compared with the AR-based estimator.

Item Type:Citation Index Journal
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Departments / MOR / COE:Mission Oriented Research > Health
ID Code:4708
Deposited By: Assoc Prof Dr Nidal Kamel
Deposited On:21 Mar 2011 07:42
Last Modified:19 Jan 2017 08:27

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