Pansharpening of multispectral images using a TV-based super-resolution algorithm. Mateos, J., Vega, M., Molina, R., & Katsaggelos, A. K. Journal of Physics: Conference Series, 139:012022, nov, 2008. Paper doi abstract bibtex In this paper we propose a novel algorithm for the pansharpening of multispectral images based on the use of a Total Variation (TV) image prior. Within the Bayesian formulation, the proposed methodology incorporates prior knowledge on the expected characteristics of multispectral images, and uses the sensor characteristics to model the observation process of both panchromatic and multispectral images. The pansharpened multispectral images are compared with the images obtained by other parsharpening methods and their quality is assessed both qualitatively and quantitatively. © 2008 IOP Publishing Ltd.
@article{Javier2008,
abstract = {In this paper we propose a novel algorithm for the pansharpening of multispectral images based on the use of a Total Variation (TV) image prior. Within the Bayesian formulation, the proposed methodology incorporates prior knowledge on the expected characteristics of multispectral images, and uses the sensor characteristics to model the observation process of both panchromatic and multispectral images. The pansharpened multispectral images are compared with the images obtained by other parsharpening methods and their quality is assessed both qualitatively and quantitatively. {\textcopyright} 2008 IOP Publishing Ltd.},
author = {Mateos, Javier and Vega, Miguel and Molina, Rafael and Katsaggelos, Aggelos K.},
doi = {10.1088/1742-6596/139/1/012022},
issn = {1742-6596},
journal = {Journal of Physics: Conference Series},
month = {nov},
pages = {012022},
title = {{Pansharpening of multispectral images using a TV-based super-resolution algorithm}},
url = {https://iopscience.iop.org/article/10.1088/1742-6596/139/1/012022},
volume = {139},
year = {2008}
}
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