Single Image Reflection Suppression

Reflections are a common artifact in images taken through glass windows. Automatically removing the reflection artifacts after the picture is taken is an ill-posed problem. Attempts to solve this problem using optimization schemes therefore rely on various prior assumptions from the physical world. Instead of removing reflections from a single image, which has met with limited success so far, we propose a novel approach to suppress reflections. It is based on a Laplacian data fidelity term and an l(0) gradient sparsity term imposed on the output. With experiments on artificial and real-world images we show that our reflection suppression method performs better than the state-of-the-art reflection removal techniques.


Published in:
30Th Ieee Conference On Computer Vision And Pattern Recognition (Cvpr 2017), 1752-1760
Presented at:
IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017), Honolulu, Hawaï, USA, July 21-26, 2017
Year:
2017
Publisher:
New York, Ieee
ISSN:
1063-6919
ISBN:
978-1-5386-0457-1
Laboratories:




 Record created 2017-04-06, last modified 2018-09-13

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