Bregman Approach to Single Image De-Raining

László Szirmay-Kalos and Márton Tóth
Department of Control Engineering and Information Technology, Budapest University of Technology and Economics,
Budapest, Magyar Tudósok krt. 2, HUNGARY


Surveillance cameras are expected to work also in bad visibility conditions, which requires algorithmic solutions to improve the captured image and to eliminate image degradation caused by these weather conditions. Algorithms for such tasks belong to the field of computational photography and have been successful in eliminating haze, fog, motion blur, etc. This paper presents a simple algorithm to suppress rain or snow from single images. The algorithm uses energy minimization, and we propose a novel data term and a Bregman distance based regularization term reflecting the particular properties of precipitation.


De-raining, De-snowing, Bregman iteration, Total Variation, Gradient descent