Abstract

Optical satellite images are the main source of geophysical information which can be used for various land surface studies. But one of the most challenging issue faced by these images are the severe cloud contamination. As far as optical satellite images are of concern, thick clouds will completely obstructs the observation of landscape and uneven illumination caused by thin clouds will further limits the processing of optical satellite images. So a method to eliminate the impact of clouds in optical satellite images is necessary to improve the effectiveness and availability of remote sensing data for various land surface studies. In this paper, a novel methodology for removing the uneven illumination caused by thick and thin clouds is intro-duced. For this approach, multitemporal cloud contaminated optical satellite images are required with the assumption that in each image cloud cover change significantly over a short duration of time. A cloud detection algorithm in frequency domain is used to detect the cloud contaminated portions in multitemporal optical satellite images. Suitable cloud free patch from reference images for reconstructing cloud contaminated portions in target image are selected based on lower amount of cloud rate and quality assessment technique. Some experimental analysis is conducted on collected Aqua MODIS sensor captured multitemporalsatellite images. Experimental result shows that the proposed algorithm can effectively remove majority of cloud contamination within the optical satellite images. Finally quantitative measures are performed to evaluate the feasibility of the methodology.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.