Enhanced variational image dehazing

Authors: Galdran, A., Vazquez-Corral, J., Pardo, D. and Bertalmío, 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 Bertalmío, M.

Journal: SIAM J. Imaging Sci.

Volume: 8

Pages: 1519-1546

Source: DBLP