4 February 2009 Detection of reflecting surfaces by a statistical model
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Abstract
Remote sensing is widely used assess the destruction from natural disasters and to plan relief and recovery operations. How to automatically extract useful features and segment interesting objects from digital images, including remote sensing imagery, becomes a critical task for image understanding. Unfortunately, current research on automated feature extraction is ignorant of contextual information. As a result, the fidelity of populating attributes corresponding to interesting features and objects cannot be satisfied. In this paper, we present an exploration on meaningful object extraction integrating reflecting surfaces. Detection of specular reflecting surfaces can be useful in target identification and then can be applied to environmental monitoring, disaster prediction and analysis, military, and counter-terrorism. Our method is based on a statistical model to capture the statistical properties of specular reflecting surfaces. And then the reflecting surfaces are detected through cluster analysis.
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Qiang He, Chee-Hung Henry Chu, "Detection of reflecting surfaces by a statistical model", Proc. SPIE 7251, Image Processing: Machine Vision Applications II, 72510O (4 February 2009); doi: 10.1117/12.805761; https://doi.org/10.1117/12.805761
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