A Sensor Image Dehazing Algorithm Based on Feature Learning

作者：Liu, Kun^*; He, Linyuan^*; Ma, Shiping; Gao, Shan; Bi, Duyan

来源：Sensors (Switzerland), 2018, 18(8): 2606.

DOI：10.3390/s18082606

• image dehazing
• feature learning
• sparse coding
• generative adversarial networks

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

• 出版日期2018-8
• 单位中国人民解放军空军工程大学