Abstract

With the continual development of deep learning, the image processing in Internet of Things is the key technology. Nevertheless, many deep learning methods cannot deal with the special needs of Internet of Things, for example, the Internet of vehicles and ships for the traffic haze image. Particularly, haze removal in the water area, because of the influence of water vapor, is more difficult than that in the ordinary scene. And the dehazing of water area has practical value in shipping and aerial photography. Sensible dehazing effect can even ensure the safety of navigation. In this paper, a compensation textures dehazing method is presented for water alike scene. The motivation of this paper comes from the following observations. Dark channel haze removal method has a very real dehazing effect for ordinary scenes. However, due to the principle of the dark channel method, this dehazing method has a large deviation in the water alike area. Therefore, based on the classical dark channel method, this paper proposes three innovations. First, a dynamic priority method is designed. This method can calculate the priority order of patches according to the characteristics of the processed subject. Second, a compensation textures method is designed, which can compensate the special area according to the proposed priority method. Third, a new haze removal method is designed, which can effectively remove the haze of water area according to the proposed compensation textures method. The results of visual and quality experiment show that proposed method has a state-of-the-art dehazing result in the water alike area.

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