Classification Of Multi-Classed Stochastic Images Buried In Additive Noise

Zu-Han Gu; Sing H. Lee

doi:10.1117/12.936937

8 January 1987 Classification Of Multi-Classed Stochastic Images Buried In Additive Noise

Zu-Han Gu, Sing H. Lee

Proceedings Volume 0700, 1986 Intl Optical Computing Conf; (1987) https://doi.org/10.1117/12.936937
Event: 1986 International Computing Conference, 1986, Jerusalem, Israel

Abstract

The Optimal Correlation Filter for the discrimination or classification of multi-class stochastic images buried in additive noise is designed. We consider noise in images as the (K+1)th class of stochastic image so that the K-class with noise problem becomes a problem of (K+1)-classes: K-class without noise plus the (K+1)th class of noise. Experimental verifications with both low frequency background noise and high fre-quency shot noise show that the new filter design is reliable.

Citation Download Citation

Zu-Han Gu and Sing H. Lee "Classification Of Multi-Classed Stochastic Images Buried In Additive Noise", Proc. SPIE 0700, 1986 Intl Optical Computing Conf, (8 January 1987); https://doi.org/10.1117/12.936937

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