Robust automatic recognition system of manmade areas using morphological segmentation and very-high-resolution remotely sensed data

M. Pesaresi; Ioannis Kanellopoulos

doi:10.1117/12.331870

4 December 1998 Robust automatic recognition system of manmade areas using morphological segmentation and very-high-resolution remotely sensed data

M. Pesaresi, Ioannis Kanellopoulos

Author Affiliations +

Proceedings Volume 3500, Image and Signal Processing for Remote Sensing IV; (1998) https://doi.org/10.1117/12.331870
Event: Remote Sensing, 1998, Barcelona, Spain

Abstract

Imagery from the new generation very high-resolution sensors, will increase dramatically the geometric scene resolution but it will also decrease the accuracy of the For urban applications in particular, with the spatial properties of the new sensors it will be possible to recognize not only a generic texture window with specific urban characteristics, but also to detect in detail the objects that constitute the 'urban theme.' In this paper a segment based segmentation procedure is presented, based on the gray-scale geodesic morphological transformation and has been successfully utilized to detect built-up objects using only the 5 m spatial resolution panchromatic data of the IRS1-C satellite. The imagery is subsequently classified on a segment basis using a multi-layer perceptron neural network classifier.

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M. Pesaresi and Ioannis Kanellopoulos "Robust automatic recognition system of manmade areas using morphological segmentation and very-high-resolution remotely sensed data", Proc. SPIE 3500, Image and Signal Processing for Remote Sensing IV, (4 December 1998); https://doi.org/10.1117/12.331870

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