Visibility in Bad Weather from a Single Image. Robby T. Tan Imperial College London CVPR. 2008. Outline . Introduce Model Algorithm Result Future work and conclusion. x is the 2D spatial location. L∞ is the atmospheric light. ρ is the reflectance of an object in the image .
Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.
Visibility in Bad Weather from a Single Image Robby T. Tan Imperial College London CVPR. 2008
Outline • Introduce • Model • Algorithm • Result • Future work and conclusion
x is the 2D spatial location. • L∞ is the atmospheric light. • ρ is the reflectance of an object in the image. • β is the atmospheric attenuation coefficient. • d is the distance between an object in the image and the observer.
Define image chromaticityAssume distant (d = ∞) , since e^-βd = 0 , light chromaticityAssume no effect of scattering particles e^-βd = 1 , object chromaticity
By utilizing the light chromaticity (α) we can transform the color of the atmospheric light of the input image into white color • Color vectors：
AirlightSmoothness Constraint • Data term • Smooth term
Future work and conclusion • 失真情形