Enhanced variational image dehazing

Images obtained under adverse weather conditions, such as haze or fog, typically/nexhibit low contrast and faded colors, which may severely limit the visibility within the scene. Unveiling/nthe image structure under the haze layer and recovering vivid colors out of a single image/nremains a challeng...

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Detalles Bibliográficos
Autores: Galdran, Adrian, Vazquez-Corral, Javier, Pardo, David, Bertalmío, Marcelo
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2015
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10230/26896
Acceso en línea:http://hdl.handle.net/10230/26896
http://dx.doi.org/10.1137/15M1008889
Access Level:acceso abierto
Palabra clave:Image dehazing
Perceptual color correction
Contrast enhancement
Variational image processing
Visibility enhancement
Descripción
Sumario:Images obtained under adverse weather conditions, such as haze or fog, typically/nexhibit low contrast and faded colors, which may severely limit the visibility within the scene. Unveiling/nthe image structure under the haze layer and recovering vivid colors out of a single image/nremains a challenging task, since the degradation is depth-dependent and conventional methods are/nunable to overcome this problem. In this work, we extend a well-known perception-inspired variational/nframework for single image dehazing. Two main improvements are proposed. First, we replace/nthe value used by the framework for the grey-world hypothesis by an estimation of the mean of/nthe clean image. Second, we add a set of new terms to the energy functional for maximizing the/ninter-channel contrast. Experimental results show that the proposed Enhanced Variational Image/nDehazing (EVID) method outperforms other state-of-the-art methods both qualitatively and quantitatively./nIn particular, when the illuminant is uneven, our EVID method is the only one that recovers/nrealistic colors, avoiding the appearance of strong chromatic artifacts.