Abstract
In this paper, we extended our investigation on an optimal algorithm for removing the thin cloud cover from remote sensing images by using a level set based approach on an image such as on the multitemporal LANDSAT 8 OLI images. Here, we use the K-means clustering method to divide the cloud-free images into several homogeneous regions. And then, we employed the level set method to determine the cloud thickness level in each pixel in a cloudy image. After that, we reconstructed the area under the thin cloud under the assumption that the homogeneous regions from both cloud-free and cloudy images are similar. The experiments showed that the method can address this problem with the satisfying result.
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