Title :
Fast single image fog removal using the adaptive Wiener filter
Author :
Gibson, Kristofor B. ; Nguyen, Truong Q.
Author_Institution :
Electr. & Comput. Eng. Dept., UC San Diego, La Jolla, CA, USA
Abstract :
We present in this paper a fast single image defogging method that uses a novel approach to refining the estimate of amount of fog in an image with the Locally Adaptive Wiener Filter. We provide a solution for estimating noise parameters for the filter when the observation and noise are correlated by decorrelating with a naively estimated defogged image. We demonstrate our method is 50 to 100 times faster than existing fast single image defogging methods and that our proposed method subjectively performs as well as the Spectral Matting smoothed Dark Channel Prior method.
Keywords :
Wiener filters; adaptive filters; fog; image denoising; image enhancement; parameter estimation; fast-single-image defogging method; fast-single-image fog removal; image fog amount estimate refining; locally adaptive Wiener filter; noise parameter estimation; spectral matting smoothed dark channel prior method; Atmospheric modeling; Estimation; Image color analysis; Image edge detection; Image resolution; Noise; Wiener filters; Bilateral Filter; Defogging; Image Enhancement; Visibility;
Conference_Titel :
Image Processing (ICIP), 2013 20th IEEE International Conference on
Conference_Location :
Melbourne, VIC
DOI :
10.1109/ICIP.2013.6738147