Efficient Dehazing Method for Outdoor and Remote Sensing Images

Abstract

As an atmospheric phenomenon, haze significantly reduces the visibility of outdoor and remote sensing images. As remote sensing and outdoor imaging have different mechanisms, existing dehazing methods are hard to be applied for both outdoor images and remote sensing images. In this article, an efficient dehazing method is proposed which can be applied to both outdoor and remote sensing images. The proposed method has the advantages of both dehazing methods based on image enhancement and image restoration methods. To address the problem of inaccurate calculation of transmittance in existing methods, a Gaussian-weighted image fusion is introduced to obtain a refined transmittance. In addition, to solve the problem of image color distortion after dehazing, an unsharp mask method is used to correct the dehazed image. Experiments on the synthetic dataset and real dataset show that the proposed method is able to dehaze both the outdoor and remote sensing images and outperforms existing methods by visual inspection. On the RICE remote sensing image dataset, the proposed method has an image peak signal-to-noise ratio of 27.08 and structural similarity of 0.94, which are higher than other methods.

Keywords

• Dark channel prior (DCP)
• image dehazing
• image restoration
• remote sensing (RS)
• Retinex
• transmittance