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Improving Satellite Image Analysis Quality by Data Fusion

Shan yu 1 
1 PASTIS - Scene Analysis and Symbolic Image Processing
CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : Remotely sensed images are often too complex to be analyzed by a single algorithm. In this work, the author considers the problem of merging results issued from different algorithms performing the same task on a satellite image so as to improve the quality of the result. Two types of error measures are computed for each (intermediate) result to estimate its reliability: the global error measure determines whether a result is good enough to be used in the fusion process; the local error measure of each site determines hour information given by this site will be taken into account in the fusion process: site with a smaller local error measure has a higher reliability, thus has more influence on decision making in the fusion process. Map knowledge is used for evaluating the error measures
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https://hal.inria.fr/hal-01087887
Contributor : Shan Yu Connect in order to contact the contributor
Submitted on : Thursday, November 27, 2014 - 5:19:26 AM
Last modification on : Friday, February 4, 2022 - 3:15:53 AM

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Shan yu. Improving Satellite Image Analysis Quality by Data Fusion. IGARSS'95 - Geoscience and Remote Sensing Symposium, Jul 1995, Florence, Italy. pp.2164-2166, ⟨10.1109/IGARSS.1995.524137⟩. ⟨hal-01087887⟩

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