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ISPRS Int. J. Geo-Inf. 2016, 5(12), 228; doi:10.3390/ijgi5120228

Retrieval of Remote Sensing Images with Pattern Spectra Descriptors

1
Institut de Recherche en Informatique et Systèmes Aléatoires, Université Bretagne Sud, 56000 Vannes, France
2
Institute of Information Technologies, Gebze Technical University, 41400 Kocaeli, Turkey
3
Institut de Recherche en Informatique et Systèmes Aléatoires, Université Rennes 1, 35000 Rennes, France
*
Author to whom correspondence should be addressed.
Academic Editors: Beatriz Marcotegui and Wolfgang Kainz
Received: 5 June 2016 / Revised: 11 November 2016 / Accepted: 17 November 2016 / Published: 2 December 2016
(This article belongs to the Special Issue Mathematical Morphology in Geoinformatics)
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Abstract

The rapidly increasing volume of visual Earth Observation data calls for effective content based image retrieval solutions, specifically tailored for their high spatial resolution and heterogeneous content. In this paper, we address this issue with a novel local implementation of the well-known morphological descriptors called pattern spectra. They are computationally efficient histogram-like structures describing the global distribution of arbitrarily defined attributes of connected image components. Besides employing pattern spectra for the first time in this context, our main contribution lies in their dense calculation, at a local scale, thus enabling their combination with sophisticated visual vocabulary strategies. The Merced Landuse/Landcover dataset has been used for comparing the proposed strategy against alternative global and local content description methods, where the introduced approach is shown to yield promising performances. View Full-Text
Keywords: content based image retrieval; mathematical morphology; pattern spectra; remote sensing; scene description content based image retrieval; mathematical morphology; pattern spectra; remote sensing; scene description
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Bosilj, P.; Aptoula, E.; Lefèvre, S.; Kijak, E. Retrieval of Remote Sensing Images with Pattern Spectra Descriptors. ISPRS Int. J. Geo-Inf. 2016, 5, 228.

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