Speed-up single image dehazing using double dark channels

Abstract

Recent research has made significant progress in single image dehazing by using dark channel prior. We can directly estimate the thickness of the haze and recover a high quality haze-free image by using it. However, such method is inefficient when processing high resolution or high-bit-wide images because of its high computational complexity. Besides, the results are inaccurate when there are large white objects in the scene. A novel image prior is proposed in this paper to solve the above drawbacks. We develop a powerful and speed-up single image dehazing method by replacing the single dark channel with double dark channels with different scales to estimate the global atmospheric light and the transmission. Thus we can separate the method into two parts and ignore the soft matting that occupies 95% computation cost of the previous method. The experimental results show that our method is much faster than the original method and reduces the distortion caused by large white objects in the scene at the same time. Compared with previous method, our new single image dehazing method achieves the same, even better image quality with only around 1/23 computation time and saves lots of memory space.

Nighttime Haze Removal with Illumination Correction

“…We implemented our algorithm using Matlab on a Laptop with Intel Core i5 and memory of 8GB. As an example, we calculated the computational times of test images of different sizes, e. been proposed for image dehazing recently [26]- [30]. We leave it as future work to realize a faster implementation of the proposed algorithm.…”