A self-adaptive homomorphic filter method for removing thin cloud

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, homomorphic filtering can be used to remove thin cloud. The traditional method takes whole image to calculate, not time consuming only, but also destroying the information on non-cloud field. Moreover, due to the same cut-off frequency, the effect of removing different cloud is not ideal. In this paper, a self-adaptive homomorphic filter method is proposed. At first, the LIS A analyses method is used to extract cloud cover region. Secondly, by evaluating the DN value to de termine the thickness of the clouds, different cut-off frequencies are calculated. Finally, through the homomorphic filters with different cut-off frequencies, a result is calculated.