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Journal of Electronic Imaging

Single image dehazing algorithm using wavelet decomposition and fast kernel regression model
Author(s): Xie Cong-Hua; Qiao Wei-Wei; Zhang Xiu-Xiang; Zhu Feng
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Paper Abstract

In order to address the problems of discontinuity and block effect for the dehazing method based on dark channel prior, we improved this method using wavelet decomposition, fast kernel regression model, and bicubic interpolation. First, spatial resolution of the hazy image was reduced by the downsampling method with Haar wavelet decomposition. Second, the fast kernel regression model was proposed to smooth the central transmission with local neighbor transmissions. Last, the smoothed transmission for the approximation image was resized to the hazy image by the bicubic interpolation method. Experiments were carried out on synthetic hazy images with known ground truth and real-world hazy images without ground truth. The regions of sudden change of depth in the dehazed images by our method were more smooth and continuous than those of several state-of-the-art methods, and contrast of our method was higher than that of other methods. Indexes based on the concept of visibility level, mean squared error, and structural similarity of our method were better than those of other methods.

Paper Details

Date Published: 11 July 2016
PDF: 12 pages
J. Electron. Imaging. 25(4) 043003 doi: 10.1117/1.JEI.25.4.043003
Published in: Journal of Electronic Imaging Volume 25, Issue 4
Show Author Affiliations
Xie Cong-Hua, Changshu Institute of Technology (China)
Qiao Wei-Wei, Changshu Institute of Technology (China)
Soochow Univ. (China)
Zhang Xiu-Xiang, Nanjing Normal Univ. (China)
Zhu Feng, Jiangsu Univ. (China)

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