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Contextual Spatiospectral Postreconstruction of Cloud-Contaminated Images

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2 Author(s)
Souad Benabdelkader ; Dept. of Electron., Univ. of Batna, Batna ; Farid Melgani

A general method has been proposed recently for the contextual reconstruction of cloud-contaminated areas in multitemporal multispectral images. It is based on the idea of making the prediction process learn from information available in the cloud-free neighborhood of contaminated areas. Though promising, this method does not fully exploit all available information, thus leaving room for further methodological enhancements. This letter presents a postreconstruction methodology for improving the contextual reconstruction process by opportunely capturing spatial and spectral correlations characterizing the considered image. In addition, we propose a solution to a problem that has not yet been addressed in the remote sensing literature, i.e., the generation of an error map beside the reconstructed images to provide end-users with helpful indications about reconstruction reliability. Thorough experiments conducted on a multitemporal sequence of Landsat-7 ETM+ images are reported and discussed.

Published in:

IEEE Geoscience and Remote Sensing Letters  (Volume:5 ,  Issue: 2 )