Title:
|
A variational framework for single image dehazing
|
Author:
|
Galdran, Adrian; Vazquez-Corral, Javier; Pardo, David; Bertalmío, Marcelo
|
Abstract:
|
Comunicació presentada a: European Conference on Computer Vision Workshops (ECCV 2014), celebrada del 6 al 7 de setembre de 2014 a Zurich, Suïssa. |
Abstract:
|
Images captured 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 struc-
ture 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 handle this problem.
We propose to extend a well-known perception-inspired variational frame-
work [1] for the task of single image dehazing. The main modification
consists on the replacement of the value used by this framework for the
grey-world hypothesis by an estimation of the mean of the clean image.
This allows us to devise a variational method that requires no estimate of
the depth structure of the scene, performing a spatially-variant contrast
enhancement that effectively removes haze from far away regions. Exper-
imental results show that our method competes well with other state-
of-the-art methods in typical benchmark images, while outperforming
current image dehazing methods in more challenging scenarios. |
Abstract:
|
JVC and MB were supported by European Research Council, Starting Grant ref.
306337, and by Spanish grants ref. TIN2011-15954-E and ref. TIN2012-38112. |
Subject(s):
|
-Image dehazing -Image defogging -Color correction -Contrast enhancement |
Rights:
|
© Springer The final publication is available at Springer via
http://dx.doi.org/10.1007/978-3-319-16199-0_18 |
Document type:
|
Conference Object Article - Accepted version |
Published by:
|
Springer
|
Share:
|
|