Automatic cloud removal from multi-temporal SPOT images

Partial cloud cover is a severe problem in the optical remote sensing images. The problem can be mostly overcome by mosaicking the cloud-free areas of the multi-temporal images. In this paper, multidisciplinary methods are proposed to generate cloud-free mosaic images from multi-temporal SPOT images in three steps. At first, the original images are enhanced in both brightness and chromaticity. Secondly, the linear spectral unmixing method (LSU) is used to extract all cloud cover regions. Then, we choose the base image that has the least thin-cloud cover and divide the base image into grid zones. We find the thin-cloud and cloud-shadow zones in the eight neighbors of the thick-cloud zones based on the relative locations and the sun elevation angle. At last, the cloud and cloud-shadow zones of the base image are replaced by the same-location cloud-free zones on other images. Between each two zones of the base image and the replacing image, we create a transition zone. The multiscale wavelet-based fusion method is then used to fuse the pixels in the zones to generate cloud-free satellite images. Based on our complete and sophisticated approach, the high-quality fused results are produced from the source images that have variant brightness.