Removing thin cloud from remote sensing digital images based on robust kernel regression

This paper suggests a thin cloud removing approach of remote sensing image based on robust kernel regression. Due to the influence of atmosphere condition, cloud cover is one of the most disturbance factors in remote sensing image. So cloud removal is a very important step for improving the quality of the image before making analysis. Because thin cloud is the low frequency component in remote sensing images, thin cloud can be removed efficiently by using the method introduced in this paper.