Paper
28 January 2002 Using directional variance for urban area analysis on Spot 5 panchromatic images
Vincent Bessettes, Jacky Desachy
Author Affiliations +
Proceedings Volume 4541, Image and Signal Processing for Remote Sensing VII; (2002) https://doi.org/10.1117/12.454163
Event: International Symposium on Remote Sensing, 2001, Toulouse, France
Abstract
At the beginning of next year (2002), CNES will launch the SPOT 5 satellite. Before the launching, CNES has to validate the choices made for the sensors with the use of simulated images. Our study has been made as part of the use of SPOT 5 panchromatic images for urban area analysis. The objective of this study is to extract built-up urban areas and urban thoroughfares from simulated images. Looking at SPOT 5 panchromatic simulated images shows us that the grey level is not a good characteristic to discriminate buildings of the urban areas from other types of regions such as thoroughfares or nude-grounds. In the meantime, buildings define heterogeneous areas whereas thoroughfares and nude-grounds are homogeneous regions. So in order to classify built-up urban areas and thoroughfares, we suggest to use the directional variance of the image. With this end in view, we define a new operator of texture analysis, and we propose to combine it with classification algorithms and edge extraction operators. In order to validate our method, we present some results we have obtained on the city of Strasbourg, using simulated SPOT 5 images of 5m per pixel resolution, provided by CNES agency.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Vincent Bessettes and Jacky Desachy "Using directional variance for urban area analysis on Spot 5 panchromatic images", Proc. SPIE 4541, Image and Signal Processing for Remote Sensing VII, (28 January 2002); https://doi.org/10.1117/12.454163
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KEYWORDS
Buildings

Image classification

Roads

Image segmentation

Image resolution

Satellites

Edge detection

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