APPLICATION OF A NEURAL NETWORK FOR DETECTING SMALL-SIZE OBJECTS IN IMAGES WITH SPATIALLY NONSTATIONARY BACKGROUND
G.I. Gromilin1, V.P. Kosykh1, Yu.N. Siniavskii1,2, N.S. Yakovenko1
1Institute of Automation and Electrometry, Siberian Branch, Russian Academy of Sciences, Novosibirsk, Russia
2Federal Research Center for Information and Computational Technologies, Siberian Branch, Russian Academy of Sciences, Novosibirsk, Russia
Keywords: "point" object, spatially nonstationary background, neural network, detection
Abstract
The efficiency of using a neural network for detecting "point" objects whose shape is determined by the characteristics of the recording optical-electronic channel in images with a spatially nonstationary background is studied. The training data sets take into account the diversity of background situations and the variability of the shape of the signal from objects due to their movement. The results of detecting objects of different brightness and colors on real background images obtained during observation of the Earth's surface from a geostationary orbit are presented.
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