Single image dehazing using local adaptive signal processing

Jesus A. Valderrama; Victor H. Diaz-Ramirez; Vitaly Kober

doi:10.1117/12.2062770

23 September 2014 Single image dehazing using local adaptive signal processing

Jesus A. Valderrama, Victor H. Diaz-Ramirez, Vitaly Kober

Proceedings Volume 9217, Applications of Digital Image Processing XXXVII; 92171P (2014) https://doi.org/10.1117/12.2062770
Event: SPIE Optical Engineering + Applications, 2014, San Diego, California, United States

Abstract

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.

Citation Download Citation

Jesus A. Valderrama, Victor H. Diaz-Ramirez, and Vitaly Kober "Single image dehazing using local adaptive signal processing", Proc. SPIE 9217, Applications of Digital Image Processing XXXVII, 92171P (23 September 2014); https://doi.org/10.1117/12.2062770

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available