To solve the problems of color distortion and structure blurring in images acquired by\nsensors during bad weather, an image dehazing algorithm based on feature learning is put forward\nto improve the quality of sensor images. First, we extracted the multiscale structure features of the\nhaze images by sparse coding and the various haze-related color features simultaneously. Then,\nthe generative adversarial network (GAN) was used for sample training to explore the mapping\nrelationship between different features and the scene transmission. Finally, the final haze-free image\nwas obtained according to the degradation model. Experimental results show that the method has\nobvious advantages in its detail recovery and color retention. In addition, it effectively improves the\nquality of sensor images.
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