A Generalized Low-Rank Appearance Model for Spatio-temporally Correlated Rain Streaks

Yi-Lei Chen, Chiou-Ting Hsu; Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2013, pp. 1968-1975

Abstract


In this paper, we propose a novel low-rank appearance model for removing rain streaks. Different from previous work, our method needs neither rain pixel detection nor time-consuming dictionary learning stage. Instead, as rain streaks usually reveal similar and repeated patterns on imaging scene, we propose and generalize a low-rank model from matrix to tensor structure in order to capture the spatio-temporally correlated rain streaks. With the appearance model, we thus remove rain streaks from image/video (and also other high-order image structure) in a unified way. Our experimental results demonstrate competitive (or even better) visual quality and efficient run-time in comparison with state of the art.

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[bibtex]
@InProceedings{Chen_2013_ICCV,
author = {Chen, Yi-Lei and Hsu, Chiou-Ting},
title = {A Generalized Low-Rank Appearance Model for Spatio-temporally Correlated Rain Streaks},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},
month = {December},
year = {2013}
}