International Journal of Computer Vision
All the Images of an Outdoor Scene
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Contrast enhancement of images using human contrast sensitivity
APGV '06 Proceedings of the 3rd symposium on Applied perception in graphics and visualization
Pattern Recognition
Perception-based contrast enhancement of images
ACM Transactions on Applied Perception (TAP)
International Journal of Computer Vision
Deep photo: model-based photograph enhancement and viewing
ACM SIGGRAPH Asia 2008 papers
ACM SIGGRAPH 2009 Courses
ROBIO'09 Proceedings of the 2009 international conference on Robotics and biomimetics
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
WSEAS Transactions on Signal Processing
Enhancement of fog degraded images on the basis of histrogram classification
ICCOMP'10 Proceedings of the 14th WSEAS international conference on Computers: part of the 14th WSEAS CSCC multiconference - Volume II
Adaptive and nonlinear techniques for visibility improvement of hazy images
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part II
Greedy algorithm for local contrast enhancement of images
ICIAP'05 Proceedings of the 13th international conference on Image Analysis and Processing
International Journal of Computer Vision
Degradation of turbid images based on the adaptive logarithmic algorithm
Computers & Mathematics with Applications
Evaluating the effect of diffuse light on photometric stereo reconstruction
Machine Vision and Applications
Enhanced fog detection and free-space segmentation for car navigation
Machine Vision and Applications
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In daylight viewing conditions, image contrast is often significantly degraded by atmospheric aerosols such as haze and fog. This paper introduces a method for reducing this degradation in situations in which the scene geometry is known. Contrast is lost because light is scattered toward the sensor by the aerosol particles and because the light reflected by the terrain is attenuated by the aerosol. This degradation is approximately characterized by a simple, physically based model with three parameters. The method involves two steps: first, an inverse problem is solved in order to recover the three model parameters; then, for each pixel, the relative contributions of scattered and reflected flux are estimated. The estimated scatter contribution is simply subtracted from the pixel value and the remainder is scaled to compensate for aerosol attenuation. This paper describes the image processing algorithm and presents an analysis of the signal-to-noise ratio (SNR) in the resulting enhanced image. This analysis shows that the SNR decreases exponentially with range. A temporal filter structure is proposed to solve this problem. Results are presented for two image sequences taken from an airborne camera in hazy conditions and one sequence in clear conditions. A satisfactory agreement between the model and the experimental data is shown for the haze conditions. A significant improvement in image quality is demonstrated when using the contrast enhancement algorithm in conjuction with a temporal filter