RT Journal Article
T1 Enhanced variational image dehazing
A1 Galdran, Adrian
A1 Vazquez-Corral, Javier
A1 Pardo, David
A1 Bertalmío, Marcelo
AB Images obtained under adverse weather conditions, such as haze or fog, typically exhibit low contrast and faded colors, which may severely limit the visibility within the scene. Unveiling the image structure under the haze layer and recovering vivid colors out of a single image remains a challenging task, since the degradation is depth-dependent and conventional methods are unable to overcome this problem. In this work, we extend a well-known perception-inspired variational framework for single image dehazing. Two main improvements are proposed. First, we replace the value used by the framework for the gray-world hypothesis by an estimation of the mean of the clean image. Second, we add a set of new terms to the energy functional for maximizing the interchannel contrast. Experimental results show that the proposed enhanced variational image dehazing (EVID) method outperforms other state-of-the-art methods both qualitatively and quantitatively. In particular, when the illuminant is uneven, our EVID method is the only one that recovers realistic colors, avoiding the appearance of strong chromatic artifacts.
SN 1936-4954
YR 2015
FD 2015-07-28
LA eng
NO Galdran , A , Vazquez-Corral , J , Pardo , D & Bertalmío , M 2015 , ' Enhanced variational image dehazing ' , SIAM Journal on Imaging Sciences , vol. 8 , no. 3 , pp. 1519-1546 . https://doi.org/10.1137/15M1008889
NO Publisher Copyright: © 2015 Society for Industrial and Applied Mathematics.
DS TECNALIA Publications
RD 1 sept 2024