Robust Registration of Cloudy Satellite Images Using Two-Step Segmentation
Ik Hyun Lee, Muhammad Tariq Mahmood · IEEE Geoscience and Remote Sensing Letters · 2015
In this letter, we propose an effective registration method for cloudy satellite images based on global and local thresholds. First, cloud candidates are determined by using optimal threshold and κ-means clustering. Then, using the local threshold, the cloud candidates are further classified into three categories: thick clouds, thin clouds, and ground. Finally, accurate registration is performed by eliminating features relating to cloudy areas. The experiments show that the proposed method provides segmentation accuracy of 93.29%. In addition, registration accuracy is improved by 24.83%, as compared with conventional methods.