P
Paolo Gamba
Researcher at University of Pavia
Publications - 449
Citations - 11197
Paolo Gamba is an academic researcher from University of Pavia. The author has contributed to research in topics: Synthetic aperture radar & Hyperspectral imaging. The author has an hindex of 47, co-authored 438 publications receiving 9732 citations. Previous affiliations of Paolo Gamba include Sapienza University of Rome & Serco Group.
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Journal ArticleDOI
Recent Advances in Techniques for Hyperspectral Image Processing
Antonio Plaza,Jon Atli Benediktsson,Joseph W. Boardman,J. Brazile,Lorenzo Bruzzone,Gustavo Camps-Valls,Jocelyn Chanussot,Mathieu Fauvel,Mathieu Fauvel,Paolo Gamba,Anthony J. Gualtieri,Mattia Marconcini,James C. Tilton,G. Trianni +13 more
TL;DR: A seminal view on recent advances in techniques for hyperspectral image processing, focusing on the design of techniques able to deal with the high-dimensional nature of the data, and to integrate the spa- tial and spectral information.
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Comparison of Pansharpening Algorithms: Outcome of the 2006 GRS-S Data-Fusion Contest
TL;DR: Two algorithms outperform all the others, the visual analysis being confirmed by the quantitative evaluation, and they basically rely on MRA and employ adaptive models for the injection of high-pass details.
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Multiple Feature Learning for Hyperspectral Image Classification
Jun Li,Xin Huang,Paolo Gamba,Jose M. Bioucas-Dias,Liangpei Zhang,Jon Atli Benediktsson,Antonio Plaza +6 more
TL;DR: An important characteristic of the presented approach is that it does not require any regularization parameters to control the weights of considered features so that different types of features can be efficiently exploited and integrated in a collaborative and flexible way.
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Exploiting spectral and spatial information in hyperspectral urban data with high resolution
TL;DR: New methods for classification of hyperspectral remote sensing data are investigated, with the primary focus on multiple classifications and spatial analysis to improve mapping accuracy in urban areas.
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Multitemporal settlement and population mapping from Landsat using Google Earth Engine
Nirav N. Patel,Emanuele Angiuli,Paolo Gamba,Andrea E. Gaughan,Gianni Lisini,Forrest R. Stevens,Andrew J. Tatem,Andrew J. Tatem,G. Trianni +8 more
TL;DR: Results showed that the automated classification from GEE produced accurate urban extent maps, and that the integration of GEE-derived urban extents also improved the quality of the population mapping outputs.