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

Boris Escalante-Ramírez; Alejandra A. López-Caloca

doi:10.1117/12.820330

11 May 2009 Rural road extraction from SPOT images based on a Hermite transform pansharpening fusion algorithm

Boris Escalante-Ramírez, Alejandra A. López-Caloca

Author Affiliations +

Proceedings Volume 7336, Signal Processing, Sensor Fusion, and Target Recognition XVIII; 733619 (2009) https://doi.org/10.1117/12.820330
Event: SPIE Defense, Security, and Sensing, 2009, Orlando, Florida, United States

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.

Citation Download Citation

Boris Escalante-Ramírez and Alejandra A. López-Caloca "Rural road extraction from SPOT images based on a Hermite transform pansharpening fusion algorithm", Proc. SPIE 7336, Signal Processing, Sensor Fusion, and Target Recognition XVIII, 733619 (11 May 2009); https://doi.org/10.1117/12.820330

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