A high fidelity haze removal algorithm for optical satellite images using progressive transmission estimation based on the dark channel prior

摘要

In this paper, a high fidelity haze removal algorithm is proposed for optical satellite images by using progressive transmission estimation based on the dark channel prior (DCP). The transmission is estimated adaptively according to the histogram of the dark channel image and the constraint of maximum transmission. Then, the guided filter is used to refine the transmission to obtain a continuous transmission map in which the clean areas are retained as much as possible. The refined transmission is applied to each visual band to obtain the initial de-hazing image. Then, the transmission is re-evaluated for the initial de-hazing image, and a guided filter with a small window size is used to refine the re-evaluated transmission. Furthermore, the transmission is stretched with the power-law transformation (PLT). To ensure fidelity in hazy areas, the optimal stretched transmission is estimated according to the artificially selected samples, from which the final haze removal results can be achieved. Several optical satellite images are collected and tested to validate the effectiveness of the proposed method. The evaluation results demonstrate that the proposed method is superior to the traditional methods and can recover a haze-free image with high fidelity.