Single Image Haze Removal Using Dark Channel Prior

1. Single Image Haze Removal Using Dark Channel Prior CVPR 2009 報告者：黃智勇

2. Outline • Introduction • Dark Channel Prior • Haze Removal Using Dark Channel Prior • Estimating the Transmission • Soft Matting • Recovering the Scene Radiance • Estimating the Atmospheric Light • Experimental Results • Discussions and Conclusions

3. Introduction the modelwidely used to describe the formation of a haze image isas follows [16, 2, 8, 9]: I is the observed intensity J is the scene radiance Ais the global atmospheric light t is the medium transmissiondescribing

4. Introduction βis the scattering coefficient of the atmosphere. Itindicates that the scene radiance is attenuatedexponentiallywith the scene depth d.

5. Dark Channel Prior in most of the non-skypatches, at least one color channel has very low intensity atsome pixels. In other words, the minimum intensity in sucha patch should has a very low value. Formally, for an imageJ, we define Jc is a color channel of J and Ω(x) is a local patchcentered at x. we randomly select 5,000 images and manually cut out the sky regions. They are resized so that the maximum of width and height is 500 pixels and their dark channels are computed using a patch size 15×15.

6. Dark Channel Prior We can see that about 75% of the pixels in the dark channels have zero values, and the intensities of 90% of the pixels are below 25.

7. Haze Removal Using Dark Channel Prior- Estimating the Transmission we first assume that the atmospheric light A isgiven.

8. Haze Removal Using Dark Channel Prior- Estimating the Transmission Even in clear days the atmosphere is not absolutely free of any particle. So, the haze still exists when we look at distant objects. We fix it to 0.95 for all results reported in this paper.

9. Haze Removal Using Dark Channel Prior-Soft Matting We apply a soft matting algorithm [7] to refine the transmission. L is the Matting Laplacian matrix proposed by Levin [7].

10. Haze Removal Using Dark Channel Prior-Recovering the Scene Radiance A typical value of t0 is 0.1.

11. Haze Removal Using Dark Channel Prior-Estimating the Atmospheric Light The pixel with highest intensity is used as the atmospheric light in [16] We first pick the top 0.1% brightest pixels in the dark channel.

12. Experimental Results

13. Experimental Results

14. Experimental Results

15. Experimental Results

16. Discussions and Conclusions • When the scene objectsare inherently similar to the atmospheric light and noshadow is cast on them, the dark channel prior isinvalid. • The sun’s influence on thesky region, and the blueish hue near the horizon. • We intendto investigate haze removal based on these models in thefuture.