Supplementary Materials

Authors

Abstract

A fast and optimized dehazing algorithm for hazy images and videos is proposed in this work. Based on the observation that a hazy image exhibits low contrast in general, we restore the hazy image by enhancing its contrast. However, the overcompensation of the degraded contrast may truncate pixel values and cause information loss. Therefore, we formulate a cost function that consists of the contrast term and the information loss term. By minimizing the cost function, the proposed algorithm enhances the contrast and preserves the information optimally. Moreover, we extend the static image dehazing algorithm to real-time video dehazing. We reduce flickering artifacts in a dehazed video sequence by making transmission values temporally coherent. Experimental results show that the proposed algorithm effectively removes haze and is sufficiently fast for real-time dehazing applications.

Paper

download paper

Source code

Source code is available.
download source code

Data

Hazy video sequences are available.
download data

Experiental results

Image dehazing results

Image dehazing results using various

Comparative Image dehazing results

¹R. Fattal, "Single image dehazing," ACM Trans. Graph., vol. 27, no. 3, pp. 1-9, Aug. 2008.
²R. Tan, "Visibility in bad weather from a single image," in Proc. IEEE CVPR, Jun. 2008, pp. 1-8.
³J. Kopf, B. Neubert, B. Chen, M. Cohen, D. Cohen-Or, O. Deussen, M. Uyttendaele, and D. Lischinski, "Deep photo: Model-based photograph enhancement and viewing," ACM Trans. Graph., vol. 27, no. 5, pp. 1-10, Dec. 2008.
⁴J. Tarel and N. Hautiere, "Fast visibility restoration from a single color or gray level image," in Proc. IEEE ICCV, Sep. 2009, pp. 2201-2208.
⁵K. He, J. Sun, and X. Tang, "Single image haze removal using dark channel prior," IEEE Trans. Pattern Anal. Mach. Intell., vol. 33, no. 12, pp. 1956-1963, Jun. 2011.

Comparative video dehazing results

Citation