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A Physically-Based Approach to Reflection Separation: from Physical Modeling to Constrained Optimization
PrePrint
ISSN: 0162-8828
Naejin Kong, Korea Advanced Institute of Science and Technology, Daejeon
Yu-Wing Tai, Korea Advanced Institute of Science and Technology, Daejeon
Joseph S. Shin, Korea Advanced Institute of Science and Technology, Daejeon
We propose a physically-based approach to separate reflection using multiple polarized images with a background scene captured behind glass. The input consists of three polarized images, each captured from the same view point but with a different polarizer angle separated by 45 degrees. The output is the high-quality separation of the reflection and background layers from each of the input images. A main technical challenge for this problem is that the mixing coefficient for the reflection and background layers depends on the angle of incidence and the orientation of the plane of incidence, which are spatially-varying over the pixels of an image. Exploiting physical properties of polarization for a double-surfaced glass medium, we propose a multiscale scheme which automatically finds the optimal separation of the reflection and background layers. Thorough experiments, we demonstrate that our approach can generate superior results to those of previous methods.
Index Terms:
Glass,Image edge detection,Ash,Cameras,Equations,Mathematical model,Image sensors,Restoration,Computing Methodologies,Pattern Recognition,Applications,Computer vision,Image Processing and Computer Vision
Citation:
Naejin Kong, Yu-Wing Tai, Joseph S. Shin, "A Physically-Based Approach to Reflection Separation: from Physical Modeling to Constrained Optimization," IEEE Transactions on Pattern Analysis and Machine Intelligence, 25 Feb. 2013. IEEE computer Society Digital Library. IEEE Computer Society, <http://doi.ieeecomputersociety.org/10.1109/TPAMI.2013.45>
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