A novel edge-aware À-Trous filter for single image dehazing

Single image dehazing has been a particularly important and active area of research in computer vision. One of the key problems of physics-based methods is the fast estimation of the transmission. Previous single image based methods, however, require some time-consuming optimization algorithms, maki...

Full description

Saved in:
Bibliographic Details
Published in2012 IEEE International Conference on Information Science and Technology pp. 861 - 865
Main Authors Baojun Qi, Tao Wu, Hangen He
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.03.2012
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:Single image dehazing has been a particularly important and active area of research in computer vision. One of the key problems of physics-based methods is the fast estimation of the transmission. Previous single image based methods, however, require some time-consuming optimization algorithms, making them impracticable for real-time applications. In this paper, we propose a novel edge-aware filter based on the orthogonal B-spline wavelets. The filter is constructed by equipping low-pass filters with edge-stopping functions and leads to an efficient method for edge-preserving smoothing, which can be used in the transmission estimation according to our analysis of the dichromatic atmospheric scattering model and the dark channel prior. Instead of using conventional multiresolution processing which leads to halo effects in previous methods, we adjust Mallat algorithm to process signals from coarse scales to fine scales and obtain halo-free image filters without increasing any computational complexity. Compared with the bilateral filter, our method is much faster and has better behavior near the edges as illustrated by our noise removal testing. Extensive experiments on single image dehazing with comparable or better performance to the state-of-the-art techniques show the effectiveness of the proposed method.
ISBN:9781457703430
1457703432
ISSN:2164-4357
DOI:10.1109/ICIST.2012.6221770