Image Signa-to-Noise Ratio Estimation Using the Autoregressive MOdel
In the last two decades, a variety of techniques for signal-to-noise ratio (SNR) estimation in scanning electron microscope (SEM) images have been proposed. However, these techniques can be divided into two groups: first, SNR estimators of good accuracy, but based on impractical assumptions; second,...
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| Format: | Citation Index Journal |
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Published by FAMS, Inc., Foundation for Advances in Medicine and Science,at Mahwah,N .J.,U .S.A.
2004
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| Online Access: | http://eprints.utp.edu.my/4703/1/Scanning_1.PDF http://onlinelibrary.wiley.com/doi/10.1002/sca.4950260306/abstract http://eprints.utp.edu.my/4703/ |
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| Summary: | In the last two decades, a variety of techniques for signal-to-noise ratio (SNR) estimation in scanning electron microscope (SEM) images have been proposed. However, these techniques can be divided into two groups: first, SNR estimators of good accuracy, but based on impractical assumptions; second, estimators based on realistic assumptions but of poor accuracy. In this paper we propose the implementation of autoregressive (AR)-model interpolation as a solution to the problem. Unlike others, the proposed technique is based on a single SEM image and offers the required accuracy and robustness in estimating SNR values.
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