The new generation of spaceborne instruments, capable of capturing a large amount of very-high resolution images within a short revisit time, is allowing remote sensing researchers and final users to receive huge amounts of data in rather short times. Such a scenario makes it mandatory the development of techniques, as much as possible automatic, for the understanding and the effective exploitation of the available information. This contribution deals with the features extraction from Spotlight Cosmo-SkyMed SAR imagery (1 m spatial resolution) by means Multi Layer Perceptron Neural Network (MLP-NN) algorithms. For a better pixel characterization, textural parameters have been also considered as additional information for the classification procedure
DEL FRATE, F., Pratola, C., Schiavon, G., Solimini, D. (2011). Automatic features extraction in sub-urban landscape using very high resolution Cosmo-Skymed SAR images. In IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2011 (pp.3614-3617). IEEE [10.1109/IGARSS.2011.6050006].
Automatic features extraction in sub-urban landscape using very high resolution Cosmo-Skymed SAR images
DEL FRATE, FABIO;SCHIAVON, GIOVANNI;
2011-01-01
Abstract
The new generation of spaceborne instruments, capable of capturing a large amount of very-high resolution images within a short revisit time, is allowing remote sensing researchers and final users to receive huge amounts of data in rather short times. Such a scenario makes it mandatory the development of techniques, as much as possible automatic, for the understanding and the effective exploitation of the available information. This contribution deals with the features extraction from Spotlight Cosmo-SkyMed SAR imagery (1 m spatial resolution) by means Multi Layer Perceptron Neural Network (MLP-NN) algorithms. For a better pixel characterization, textural parameters have been also considered as additional information for the classification procedureI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
