Separation of Transparent Layers using Focus |
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Authors: | Yoav Y Schechner Nahum Kiryati Ronen Basri |
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Affiliation: | (1) Department of Computer Science, Columbia University, New York, NY 10027, USA;(2) Department of Electrical Engineering-Systems, Faculty of Engineering, Tel-Aviv University, Ramat-Aviv, 69978, Israel;(3) Department of Applied Mathematics, Weizmann Institute of Science, Rehovot, 76100, Israel |
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Abstract: | Consider situations where the depth at each point in the scene is multi-valued, due to the presence of a virtual image semi-reflected by a transparent surface. The semi-reflected image is linearly superimposed on the image of an object that is behind the transparent surface. A novel approach is proposed for the separation of the superimposed layers. Focusing on either of the layers yields initial separation, but crosstalk remains. The separation is enhanced by mutual blurring of the perturbing components in the images. However, this blurring requires the estimation of the defocus blur kernels. We thus propose a method for self calibration of the blur kernels, given the raw images. The kernels are sought to minimize the mutual information of the recovered layers. Autofocusing and depth estimation in the presence of semi-reflections are also considered. Experimental results are presented. |
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Keywords: | semireflections depth from focus blind deconvolution blur estimation enhancement image reconstruction and recovery inverse problems optical sectioning signal separation decorrelation |
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