New approach for road extraction from high resolution remotely sensed images using the quaternionic wavelet

Authors:
Mohamed Naouai;Atef Hamouda;Aroua Akkari;Christiane Weber
Affiliations:
Faculty of Science of Tunis, Belvdaire-Tunisia Research unit Urpah and Laboratory Image and Ville UMR7011-CNRS-University Strasbourg, Strasbourg;Faculty of Science of Tunis, Belvdaire-Tunisia Research unit Urpah;Faculty of Science of Tunis, Belvdaire-Tunisia Research unit Urpah;Laboratory Image and Ville UMR7011-CNRS-University Strasbourg, Strasbourg
Venue:
IbPRIA'11 Proceedings of the 5th Iberian conference on Pattern recognition and image analysis
Year:
2011

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Abstract

Automatic network road extraction from high resolution remotely sensed images has been under study by computer scientists for over 30 years. In fact, Conventional methods to create and update road information rely heavily on manual work and therefore are very expensive and time consuming. This paper presents an efficient and computationally fast method to extract road from very high resolution images automatically. We propose in this paper a new approach for following roads path based on a quaternionic wavelet transform insuring a good local space-frequency analysis with very important directional selectivity. In fact, the rich phase information given by this hypercomplex transform overcomes the lack of shift invariance property shown by the real discrete wavelet transform and the poor directional selectivity of both real and complex wavelet transform.