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Several researches published about artificial neural networks are connected with military problems. This research put forward ideas connected with the processing of military information to search and identify targets-automatic target recognition (ATR). A main-purpose automatic target recognition system did not exist. The research put forward here was demonstrated on military data, however it could...
Mapping the Moon's topography using Earth based radar interferometric measurements by the Goldstone Solar System Radar (GSSR) has been done several times since the mid 1990s. In 2008 we reported at this conference the generation of lunar topographic maps having approximately 4 m height accuracy at a horizontal posting of 40 m. Since then GSSR radar has been improved to allow 40 MHz bandwidth imaging...
Automatic object extraction from multi-source aerial data is a desirable property for many activities, such as detecting 3D city model changes or updating road databases. This paper applies the winner takes all (WTA) mechanism, derived from other research fields, to combine the benefits of pixel and region classification. We fuse LiDAR data and multi-spectral high-resolution images to generate the...
Depth maps captured with time-of-flight cameras have very low data quality: the image resolution is rather limited and the level of random noise contained in the depth maps is very high. Therefore, such flash lidars cannot be used out of the box for high-quality 3D object scanning. To solve this problem, we present LidarBoost, a 3D depth superresolution method that combines several low resolution...
Spatially Variant Apodization (SVA) is one of nonlinear apodization methods used for sidelobe control in SAR/ISAR or optical imagery while maintaining mainlobe resolution unchanged. In this paper, we apply SVA to process RADARSAT image and show that by using SVA one can get better resolution compared with using classic windowing techniques such as Hamming, etc. Also, we investigate the impact of SVA...
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