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Letter

A Change-Driven Image Foveation Approach for Tracking Plant Phenology

1
Institute of Computing, University of Campinas, Campinas 13083-852, Brazil
2
Department of ICT and Natural Sciences, Norwegian University of Science and Technology, Larsgårdsvegen 2, 6009 Ålesund, Norway
3
Department of Botany, Institute of Biosciences, São Paulo State University, Rio Claro 13506-900, Brazil
4
Biological and Environmental Sciences, Faculty of Natural Resources, University of Stirling, Stirling FK9 4LA, UK
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(9), 1409; https://doi.org/10.3390/rs12091409
Received: 28 March 2020 / Revised: 23 April 2020 / Accepted: 26 April 2020 / Published: 29 April 2020
(This article belongs to the Section Remote Sensing Letter)
One of the challenges in remote phenology studies lies in how to efficiently manage large volumes of data obtained as long-term sequences of high-resolution images. A promising approach is known as image foveation, which is able to reduce the computational resources used (i.e., memory storage) in several applications. In this paper, we propose an image foveation approach towards plant phenology tracking where relevant changes within an image time series guide the creation of foveal models used to resample unseen images. By doing so, images are taken to a space-variant domain where regions vary in resolution according to their contextual relevance for the application. We performed our validation on a dataset of vegetation image sequences previously used in plant phenology studies. View Full-Text
Keywords: foveal model; image foveation; hilbert curve; plant phenology tracking; space-variant image foveal model; image foveation; hilbert curve; plant phenology tracking; space-variant image
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MDPI and ACS Style

Silva, E.; Torres, R.d.S.; Alberton, B.; Morellato, L.P.C.; Silva, T.S.F. A Change-Driven Image Foveation Approach for Tracking Plant Phenology. Remote Sens. 2020, 12, 1409. https://doi.org/10.3390/rs12091409

AMA Style

Silva E, Torres RdS, Alberton B, Morellato LPC, Silva TSF. A Change-Driven Image Foveation Approach for Tracking Plant Phenology. Remote Sensing. 2020; 12(9):1409. https://doi.org/10.3390/rs12091409

Chicago/Turabian Style

Silva, Ewerton, Ricardo d.S. Torres, Bruna Alberton, Leonor P.C. Morellato, and Thiago S.F. Silva 2020. "A Change-Driven Image Foveation Approach for Tracking Plant Phenology" Remote Sensing 12, no. 9: 1409. https://doi.org/10.3390/rs12091409

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