Complex-Valued Convolutional Neural Networks for Object Detection in PolSAR data

Konferenz: EUSAR 2010 - 8th European Conference on Synthetic Aperture Radar
07.06.2010 - 10.06.2010 in Aachen, Germany

Tagungsband: EUSAR 2010

Seiten: 4Sprache: EnglischTyp: PDF

Persönliche VDE-Mitglieder erhalten auf diesen Artikel 10% Rabatt

Hänsch, Ronny; Hellwich, Olaf (Computer Vision and Remote Sensing, Technische Universität Berlin, FR3-1, Franklinstr. 28/29, 10587 Berlin, Germany)

Detection methods for generic object categories, which are more sophisticated than pixel-wise classification, have been rarely introduced to polarimetric synthetic aperture radar (PolSAR) images. Despite the great success in other computer vision applications, the transfer to PolSAR data has been delayed due to the different statistical properties. This paper provides a first investigation of Complex-Valued Convolutional Neural Networks (CC-NN) for object recognition in PolSAR data. Although an architecture with only one single convolutional layer was used, the results are already superior to those obtained by a standard complex-valued neural network.