Machine Vision and Applications
Guest editorial: Image fusion: Advances in the state of the art
Information Fusion
Multiscale shape and detail enhancement from multi-light image collections
ACM SIGGRAPH 2007 papers
A gentle introduction to bilateral filtering and its applications
ACM SIGGRAPH 2007 courses
Edge-preserving decompositions for multi-scale tone and detail manipulation
ACM SIGGRAPH 2008 papers
ACM SIGGRAPH 2008 papers
Deep photo: model-based photograph enhancement and viewing
ACM SIGGRAPH Asia 2008 papers
Designing color filter arrays for the joint capture of visible and near-infrared images
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Contrast restoration of weather degraded images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Designing color filter arrays for the joint capture of visible and near-infrared images
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Automatic skin enhancement with visible and near-infrared image fusion
Proceedings of the international conference on Multimedia
A fast semi-inverse approach to detect and remove the haze from a single image
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part II
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume 2
Semantic image segmentation using visible and near-infrared channels
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume 2
Optimized contrast enhancement for real-time image and video dehazing
Journal of Visual Communication and Image Representation
Robust blind motion deblurring using near-infrared flash image
Journal of Visual Communication and Image Representation
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In landscape photography, distant objects often appear blurred with a blue color cast, a degradation caused by atmospheric haze. To enhance image contrast, pleasantness and information content, dehazing can be performed. We propose that fusing a visible and an near-infrared (NIR) image of the same scene results in a dehazed color image without the need for haze or airlight detection or the generation of depth maps. This is achieved through a multiresolution approach using edge-preserving filtering to minimize artifacts. The near-infrared part of the spectrum is easy to acquire with normal digital cameras. The NIR images are generally devoid of haze as it is an inherent function of the wavelengths. Experiments on real images validate our approach.