Abstract
Reconstruction of missing information in any satellite imagery is very important. Without correct information it is very difficult to identify the area in remote sensing images. In general, there are three different types of noises in satellite imagery such as dead pixels and thick cloud cover. The Failure in Instruments such as Aqua MODIS BAND-6 instrument and ETM+ SLC (Scan Line Corrector)-off condition will lead to missing of information. The existing model consists of Double weighted low rank model Algorithm which is a time taking and less efficient model. In this paper, reconstruction of information in satellite image got done using STS-CNN (Spatial-Temporal-Spectral Convolution Neural Network), which is very efficient and uses faster network for reconstruction of information in satellite imagery.
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 callDisclaimer: 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.
