Fast Single Image Reflection Suppression via Convex Optimization

Yang Yang, Wenye Ma, Yin Zheng, Jian-Feng Cai, Weiyu Xu; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019, pp. 8141-8149

Abstract


Removing undesired reflections from images taken through the glass is of great importance in computer vision. It serves as a means to enhance the image quality for aesthetic purposes as well as to preprocess images in machine learning and pattern recognition applications. We propose a convex model to suppress the reflection from a single input image. Our model implies a partial differential equation with gradient thresholding, which is solved efficiently using Discrete Cosine Transform. Extensive experiments on synthetic and real-world images demonstrate that our approach achieves desirable reflection suppression results and dramatically reduces the execution time compared to the state of the art.

Related Material


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[bibtex]
@InProceedings{Yang_2019_CVPR,
author = {Yang, Yang and Ma, Wenye and Zheng, Yin and Cai, Jian-Feng and Xu, Weiyu},
title = {Fast Single Image Reflection Suppression via Convex Optimization},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2019}
}