Show simple item record

dc.contributor.authorGaldran, A.
dc.contributor.authorVazquez-Corral, J.
dc.contributor.authorPardo, D.
dc.contributor.authorBertalmio, M.
dc.description.abstractImages 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.
dc.rightsReconocimiento-NoComercial-CompartirIgual 3.0 Españaen_US
dc.subjectContrast enhancement
dc.subjectImage dehazing
dc.subjectPerceptual color correction
dc.subjectVariational image processing
dc.subjectVisibility enhancement
dc.titleHigh order discontinuous finite-volume/finite-element method for CFD applications
dc.journal.titleSIAM Journal on Imaging Sciencesen_US

Files in this item


This item appears in the following Collection(s)

Show simple item record

Reconocimiento-NoComercial-CompartirIgual 3.0 España
Except where otherwise noted, this item's license is described as Reconocimiento-NoComercial-CompartirIgual 3.0 España