Thin Cloud Removal Using Cirrus Spectral Property for Remote Sensing Images

Abstract

The atmosphere and cloud affects the quality of multi-spectral remote sensing images. At present, algorithms and software for atmospheric correction are widely used, but removing the effects of clouds in multi-spectral remote sensing images is still a major challenge, this paper presents a study of utilizing the cirrus band for this purpose. A cloud removal algorithm, using the spectral property of cirrus clouds, is developed for thin cloud contamination correction. Taking a Landsat-8 image affected by cloud as an example, after the cloud removal algorithm is executed, the thin cloud is removed. Use a reference image without cloud influence to further verify the cloud removal results. In a homogenous surface area, there is a certain linear relationship between the DN value of the visible band and the cirrus band. After cloud removal, the spatial correlation coefficients are all above 0.87, which is significantly higher than that before. The change of reflectance in each band and the improvement of spatial correlation coefficient fully verify the effectiveness and reliability of the algorithm.