A local adaptive algorithm for single image dehazing is presented. The algorithm is able to estimate a dehazed image from an observed hazed scene by solving an objective function whose parameters are adapted to local statistics of the hazed image inside a moving window. The proposed objective function is based on a trade-off among several local rank order statistics of the dehazed signal and the mean-squared-error between the hazed and dehazed signals. In order to achieve a high-rate signal processing, the proposed algorithm is implemented in a graphics processing unit (GPU) exploiting massive parallelism. Experimental results obtained with a laboratory prototype are presented, discussed, and compared with those results obtained with existing single image dehazing methods in terms of objective metrics and computational complexity.

Date Published: 23 September 2014
PDF: 10 pages
Proc. SPIE 9217, Applications of Digital Image Processing XXXVII, 92171P (23 September 2014); doi: 10.1117/12.2062770

Published in SPIE Proceedings Vol. 9217:
Applications of Digital Image Processing XXXVII
Andrew G. Tescher, Editor(s)