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Proceedings Paper

Spatial and temporal satellite data fusion with morphological pyramids for terrestrial surfaces survey
Author(s): Florence Laporterie; Guy Flouzat; Olivier Amram
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Paper Abstract

Nowadays, terrestrial dynamics study is more and more often performed with the help of satellite sensors. Usually, vegetation cover surveys are performed with wide field of view sensors, because of their high temporal resolution. However, a high spatial resolution will be appreciable to distinguish each component in a landscape. We propose to create merged images combining both sensors: our fusion method is based on both theories of pyramid algorithms and mathematical morphology. Let call HR (resp. BR) the spatial resolution of the high resolution (resp. coarse) sensor image, for example SPOT 4 HRVIR and VEGETATION. The principle is : 1) To decompose the high resolution image into a low-frequency and several high-frequencies images (HFI). 2) To perform the inverse transform on the HFI images and the coarse resolution sensor data and produce the merged image. Consequently, from a temporal set of VEGETATION data and from a few HRVIR scenes, we are able to create 20m (or less) resolution synthesis data having the temporal repetitivity of the VEGETATION data set.

Paper Details

Date Published: 28 January 2002
PDF: 12 pages
Proc. SPIE 4541, Image and Signal Processing for Remote Sensing VII, (28 January 2002); doi: 10.1117/12.454154
Show Author Affiliations
Florence Laporterie, Ctr. d'Etudes Spatiales de la Biosphere/Ecole Nationale de la Statistique (France)
Guy Flouzat, Ctr. d'Etudes Spatiales de la Biosphere (France)
Olivier Amram, Univ. Paul Sabatier (France)

Published in SPIE Proceedings Vol. 4541:
Image and Signal Processing for Remote Sensing VII
Sebastiano Bruno Serpico, Editor(s)

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