Rural road extraction from SPOT images based on a Hermite transform pansharpening fusion algorithm
Por:
Escalante-Ramírez B., López-Caloca A.A.
Publicada:
1 ene 2009
Resumen:
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. © 2009 SPIE.
Filiaciones:
Escalante-Ramírez B.:
Universidad Nacional Autónoma de México, Facultad de Ingeniería, Cd. Universitaria, México, D.F. 04510, Mexico
Centro de Investigación en Geografía y Geomática Ing. Jorge L. Tamayo, A.C. Contoy 137, Lomas de Padierna, México, D.F., 14240, Mexico
López-Caloca A.A.:
Centro de Investigación en Geografía y Geomática Ing. Jorge L. Tamayo, A.C. Contoy 137, Lomas de Padierna, México, D.F., 14240, Mexico
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