Single Image Reflection Suppression

Nikolaos Arvanitopoulos, Radhakrishna Achanta, Sabine Susstrunk; Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017, pp. 4498-4506

Abstract


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-zero 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.

Related Material


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[bibtex]
@InProceedings{Arvanitopoulos_2017_CVPR,
author = {Arvanitopoulos, Nikolaos and Achanta, Radhakrishna and Susstrunk, Sabine},
title = {Single Image Reflection Suppression},
booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {July},
year = {2017}
}