No-Reference Assessment on Haze for Remote-Sensing Images

Assessment on haze can filter out images with dense haze to improve the reliability of remote-sensing image interpretation. In this letter, a novel no-reference haze assessment method based on haze distribution is proposed for remote-sensing images. First, range channel of an image is defined and the haze distribution map (HDM) is extracted from the hazy image. Then, the haze assessment metric HDM-based haze assessment (HDMHA) is designed according to the HDM. Finally, the degree of haze in remote-sensing images is predicted using the proposed metric. In order to objectively verify the effectiveness of the proposed metric HDMHA, a method of simulating hazy remote-sensing images based on the haze imaging model is proposed in this letter, and the simulated hazy images are greatly similar to real ones in vision. A series of experiments are done on both real images and simulated images, and the results show that the proposed metric achieves good consistency when compared with subjective experiments and outperforms typical blind image quality assessment methods.