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심재영

Sim, Jae-Young
Visual Information Processing Lab.
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Reflection removal using low-rank matrix completion

Author(s)
Han, Byeong-JuSim, Jae-Young
Issued Date
2017-07-22
DOI
10.1109/CVPR.2017.412
URI
https://scholarworks.unist.ac.kr/handle/201301/32750
Fulltext
http://ieeexplore.ieee.org/document/8099895/
Citation
IEEE Conference on Computer Vision and Pattern Recognition, pp.3872 - 3880
Abstract
The images taken through glass often capture a target transmitted scene as well as undesired reflected scenes. In this paper, we propose a low-rank matrix completion algorithm to remove reflection artifacts automatically from multiple glass images taken at slightly different camera locations. We assume that the transmitted scenes are more dominant than the reflected scenes in typical glass images. We first warp the multiple glass images to a reference image, where the gradients are consistent in the transmission images while the gradients are varying across the reflection images. Based on this observation, we compute a gradient reliability such that the pixels belonging to the salient edges of the transmission image are assigned high reliability. Then we suppress the gradients of the reflection images and recover the gradients of the transmission images only, by solving a low-rank matrix completion problem in gradient domain. We reconstruct an original transmission image using the resulting optimal gradient map. Experimental results show that the proposed algorithm removes the reflection artifacts from glass images faithfully and outperforms the existing algorithms on typical glass images.
Publisher
30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017

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