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GPU Framework for Change Detection in Multitemporal Hyperspectral Images

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Abstract

Nowadays, it is increasingly common to detect land cover changes using remote sensing multispectral images captured at different time-frames over the same area. A large part of the available change detection (CD) methods focus on pixel-based operations. The use of spectral–spatial techniques helps to improve the accuracy results but also implies a significant increase in processing time. In this paper, a Graphic Processor Unit (GPU) framework to perform object-based CD in multitemporal remote sensing hyperspectral data is presented. It is based on Change Vector Analysis with the Spectral Angle Mapper distance and Otsu’s thresholding. Spatial information is taken into account by considering watershed segmentation. The GPU implementation achieves real-time execution and speedups of up to 46.5\(\times \) with respect to an OpenMP implementation.

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Notes

  1. The datasets along with the reference maps created and some experimental results can be downloaded from: https://wiki.citius.usc.es/hiperespectral:cva.

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Acknowledgements

This work has received financial support from the Ministry of Science and Innovation, Government of Spain, co-funded by the FEDER funds of the European Union, under Contracts TIN2013-41129-P and TIN2016-76373-P; Xunta de Galicia, Programme for Consolidation of Competitive Research Groups Ref. 2014/008; the Consellería de Cultura, Educación e Ordenación Universitaria (Accreditation 2016-2019, ED431G/08); and the European Regional Development Fund (ERDF).

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Authors and Affiliations

  1. Centro Singular de Investigación en Tecnoloxías da Información (CiTIUS), Universidade de Santiago de Compostela, Santiago de Compostela, Spain

    Javier López-Fandiño, Dora B. Heras & Francisco Argüello

  2. GIPSA-lab, Institute of Engineering, CNRS, Grenoble INP, Université Grenoble Alpes, 38000, Grenoble, France

    Mauro Dalla Mura

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  1. Javier López-Fandiño
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  2. Dora B. Heras
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  3. Francisco Argüello
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Correspondence to Javier López-Fandiño.

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López-Fandiño, J., B. Heras, D., Argüello, F. et al. GPU Framework for Change Detection in Multitemporal Hyperspectral Images. Int J Parallel Prog 47, 272–292 (2019). https://doi.org/10.1007/s10766-017-0547-5

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