Enhanced variational image dehazing
Authors: Galdran, A., Vazquez-Corral, J., Pardo, D. and BertalmÃo, M.
Journal: SIAM Journal on Imaging Sciences
Volume: 8
Issue: 3
Pages: 1519-1546
eISSN: 1936-4954
DOI: 10.1137/15M1008889
Abstract: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.
Source: Scopus
Enhanced Variational Image Dehazing
Authors: Galdran, A., Vazquez-Corral, J., Pardo, D. and Bertalmio, M.
Journal: SIAM JOURNAL ON IMAGING SCIENCES
Volume: 8
Issue: 3
Pages: 1519-1546
ISSN: 1936-4954
DOI: 10.1137/15M1008889
Source: Web of Science (Lite)
Enhanced Variational Image Dehazing.
Authors: Galdran, A., Vazquez-Corral, J., Pardo, D. and BertalmÃo, M.
Journal: SIAM J. Imaging Sci.
Volume: 8
Pages: 1519-1546
DOI: 10.1137/15M1008889
Source: DBLP