Multitemporal Segmentation And Analysis In Remote Sensing

Robert Jeansoulin; Eric Cals; Jean Claude Darcos

doi:10.1117/12.935275

26 October 1983 Multitemporal Segmentation And Analysis In Remote Sensing

Robert Jeansoulin, Eric Cals, Jean Claude Darcos

Proceedings Volume 0397, Applications of Digital Image Processing V; (1983) https://doi.org/10.1117/12.935275
Event: 1983 International Technical Conference/Europe, 1983, Geneva, Switzerland

Abstract

As a consequence of the increasing number of multi-temporal and multi-source images, in remote sensing, the need of new concepts and techniques to use the time dimension, is growing rapidly up. The forecoming french satellites SPOT,for the observation of the Earth, will speed up the flow of high-resolution and repetitive data. This paper focuses on the multitemporal segmentation, extraction and analysis of remote sensing images, as a part of geometric reasoning and scene understanding. In the context of an agricultural experiment, the "Lauragais project", the following features are described: - how to individualize entities (parcels of land), on each mono-temporal image : a non-exhaustive multispectral segmentation, based on fuzzy sets approach. - how to give a geometric description of the spatial relations between the segmented entities : a geometric database to access image data on an entity-by-entity basis. - how to compare these geometric descriptions, from date to date, and to give a multitemporal description of the landscape, by mixing all these segmentation results, in a training set, for a new classification scheme.

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Robert Jeansoulin, Eric Cals, and Jean Claude Darcos "Multitemporal Segmentation And Analysis In Remote Sensing", Proc. SPIE 0397, Applications of Digital Image Processing V, (26 October 1983); https://doi.org/10.1117/12.935275

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KEYWORDS

Image segmentation

Fuzzy logic

Remote sensing

Image processing

Radiometry

Vegetation

Binary data

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