A New Haze Removal Algorithm for Single Urban Remote Sensing Image

The remote sensing imaging detection technology is an important means to effectively monitor and manage urban environment and resources, and remote sensing images are an important data source of smart city and digital city. The existence of haze has a serious impact on the quality of optical remote sensing image acquisition, resulting in remote sensing image blurred, detail information loss, contrast decreased and color distortion. To reduce the impact of haze and give full play to the value of remote sensing images, a new urban remote sensing haze removal (URSHR) algorithm is proposed in this paper, which combines the image phase consistency feature, multi-scale Retinax theory and histogram characteristic. In URSHR method, firstly the image haze is removed by using multi-scale Retinex theory and histogram characteristic, and then the detail information of the image is enhanced by using the phase consistency features, finally they are fused with the multi-scale wavelet transform. It achieves the purpose of both removing haze and enhancing geometric detail information. The many verification experiments were carried out by using real urban remote sensing image data, and good results were obtained. This shows that the new algorithm is a feasible and effective for urban remote sensing image haze removal, and it has good application and promotion value.