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Proceedings Paper

Rural road extraction from SPOT images based on a Hermite transform pansharpening fusion algorithm
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Paper Abstract

Roads are a necessary condition for the social and economical development of regions. We present a methodology for rural road extraction from SPOT images. Our approach is centered in a fusion algorithm based on the Hermite transform that allows increasing the spatial resolution to 2.5 m. The Hermite transform is an image representation model that mimics some of the more important properties of human vision such as multiresolution and the Gaussian derivative model of early vision. Analyzing the directional energy of the expansion coefficients allows classifying the image according to the local pattern dimensionality; roads are associated to 1D patterns.

Paper Details

Date Published: 11 May 2009
PDF: 8 pages
Proc. SPIE 7336, Signal Processing, Sensor Fusion, and Target Recognition XVIII, 733619 (11 May 2009); doi: 10.1117/12.820330
Show Author Affiliations
Boris Escalante-Ramírez, Univ. Nacional Autónoma de México (Mexico)
Ctr. de Investigación en Geografía y Geomática (Mexico)
Alejandra A. López-Caloca, Ctr. de Investigación en Geografía y Geomática (Mexico)


Published in SPIE Proceedings Vol. 7336:
Signal Processing, Sensor Fusion, and Target Recognition XVIII
Ivan Kadar, Editor(s)

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