Cloud removal for optical images using SAR structure data
Cheng Zhu, Zhiqin Zhao, Xiaozhang Zhu, Zaiping Nie, Qing Huo Liu · 2016
Cloud cover impacts the quality of optical remote sensing images. Generally, temporal methods and inpainting methods are used to remove the clouds. The temporal methods reconstruct cloudy areas via a series of multi-temporal images, thus suffer from the assumption that the landscape does not change over a period of time. The inpainting methods fill the areas via image patches from the image itself. Lacking prior information of the cloudy areas, these methods are limited in reconstructing accuracy, especially when clouds lie on the boundaries of two types of landscapes. We propose a new method based on the inpanting method which take the SAR (Synthetic Aperture Radar) images as a prior structure information of contaminated. Using information from two kinds of images acquired at the same time, the proposed method also avoids inaccuracy caused by land changes in temporal methods. This idea has been demonstrated by experiments carried out on Theme Mapper data and Sentinel-1A data. In terms of RMSE (Root Mean Square Error), the proposed method is evaluated and compared with several other cloud removal algorithm.