Published Paper Details:

ABSTRACT - Fog and haze make the photo degraded, and seriously affect the ordinary operation of the records device inside the fields of military, transportation and protection monitoring. Under this condition, the image de-fogging is of great significance. In order to meet the needs of real-time processing of existing video's de fogging process, a recognition algorithm based on recurrent neural network is proposed in this project. We use sparse automatic coding machine to extract the texture features of the image, and extract all kinds of fog related color features. Then, we use the recurrent neural network to implement sample training process, and we obtain the mapping relationship between texture structure features and color features and scene depth, and then we estimate the scene deep map of fog images. Finally, the atmospheric scattering model is used to recover the fog free image according to the scene deep map. Experiments show that the proposed algorithm can effectively obtain the scene depth of the image, and recover the ideal fog free image