An Online Application for Defogging of Videos and Images based on RNN

Most of the time climate decides the quality of an image.so, the situation of fog and haze make the image degraded. that is why there is a need of de fogging of an image The de-fogging system will favor the normal operations of the information system in the fields of military, transportation and safety monitoring. for the de-fogging purpose we are using a recognition algorithm based on recurrent neural network. . At present, the mainstream image de-fogging algorithm mainly uses a variety of fog related color features, however, different color prior knowledge often has its own scene limitation. 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. Also, we are giving an interface with telegram application.