A haze removal algorithm combining fractional differential, dark channel prior and Retinex

被引：1

作者：

Ma R.-G. ^{[1
]}

Wang W.-X. ^{[1
]}

Liu W. ^{[1
]}

Zhang Y. ^{[1
]}

Xu L. ^{[1
]}

机构：

[1] School of Information Engineering, Chang'an University, Xi'an, 710064, Shaanxi

来源：

Huanan Ligong Daxue Xuebao/Journal of South China University of Technology (Natural Science) | 2016年 / 44卷 / 09期

基金：

中国国家自然科学基金;

关键词：

Dark channel prior; Fractional differential; Haze; Image enhancement; Multi-scale variation; Retinex transform;

D O I：

10.3969/j.issn.1000-565X.2016.09.003

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

In order to improve the clarity of haze images, this paper proposes a haze removal algorithm combining the fractional differential, the dark channel prior and the Retinex. In the algorithm, a high-texture haze image is processed first through the fractional differential and then through the dark channel prior. Moreover, on the basis of the depth map obtained through the dark channel prior, the Retinex scales are calculated in each part of the processed image. Finally, the image enhancement result is got by performing the Retinex transform of the image after the fractional differential operation. The test results of a number of haze images show that the new algorithm can effectively improve the clarity of haze images with less Retinex halo phenomena, and in comparison with the existing dark channel prior and multi-scale Retinex algorithms, it has a higher processing speed and a better image enhancement effect for the haze images of the high texture and great scene depth difference. © 2016, Editorial Department, Journal of South China University of Technology. All right reserved.

引用

页码：16 / 23

页数：7

共 20 条

[1]

Li Z., Zheng J., Zhu Z., Et al., Weighted guided image filtering, IEEE Transactions on Image Processing, 24, 1, pp. 120-129, (2015)

[2]

Fan X., Wang Y., Gao R., Et al., Haze editing with natural transmission, The Visual Computer, 32, 1, pp. 137-147, (2016)

[3]

Guo F., Cai Z.-X., Xie B., Et al., New algorithm of automatic haze removal for single image, Journal of Image and Graphics, 16, 4, pp. 516-521, (2011)

[4]

Land E.H., An alternative technique for the computation of the designator in the Retinex theory of color vision, Proceedings of the National Academy of Sciences of the United States of America, 83, 10, pp. 3078-3080, (1986)

[5]

Jobson D.J., Rahman Z., Woodell G.A., A multiscale Retinex for bridging the gap between color images and the human observation of scenes, IEEE Transactions on Image Processing, 6, 7, pp. 965-976, (1997)

[6]

Liu G.-P., Zhao M., An adaptive single scale Re-tinex scheme for image enhancement based on luminance, Opto-Electronic Engineering, 38, 2, pp. 71-77, (2011)

[7]

Xu X., Chen Q., Wang P.-A., Et al., A fast halo-free image enhancement method based on Retinex, Journal of Computer-Aided Design & Computer Graphics, 20, 10, pp. 1325-1331, (2008)

[8]

Morel J.M., Petro A.B., Sbert C., A PDE formalization of Retinex theory, IEEE Transactions on Image Processing, 19, 11, pp. 2825-2837, (2010)

[9]

Wang W.X., Li W.S., Yu X., Fractional differential algorithms for rock fracture images, The Imaging Science Journal, 60, 2, pp. 103-111, (2012)

[10]

Zhang S., Wang W., Liu S., Et al., Image enhancement on fractional differential for road traffic and aerial images under bad weather and complicated situations, Transportation Letters: The International Journal of Transportation Research, 6, 4, pp. 197-205, (2014)

← 1 2 →