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Title
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Separation of Reflection Components by Kernel Independent Component Analysis
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Author
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Masaki Yamazaki, Yen Wei Chen, Gang Xu
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Citation |
Vol. 6 No. 6 pp. 7-12
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Abstract
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When we view a scene through transparent glass, the image is a linear superposition of two images, a real image observed through a glass and a virtual image reflected on it. We can separate the reflections by a polarization and Independent Component Analysis (ICA). Since the image observed through digital camera is non-linearly transformed by gamma correction etc, it may cause error in image processing for image analysis and measurement. The kernel-based methods are effective for such non-linearity. In this paper, we remove the reflections by using Kernel Independent Component Analysis (KICA) and show that KICA is more effective than ICA even if the observed image is non-linearly transformed by camera.
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Keywords
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Separating Reflections, Independent Component Analysis, Camera¡¯s Non-linearity, Kernel Independent Component Analysis
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URL
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http://paper.ijcsns.org/07_book/200606/200606A02.pdf
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