DOI: 10.17586/1023-5086-2020-87-06-43-50
УДК: 528.8.04
Modified method of orthogonal projection for object recognition in multispectral analysis
Full text «Opticheskii Zhurnal»
Full text on elibrary.ru
Publication in Journal of Optical Technology
Герус А.В., Панова О.Ю., Саворский В.П. Модифицированный метод ортогональной проекции для выявления объектов в многоспектральном анализе // Оптический журнал. 2020. Т. 87. № 6. С. 43–50. http://doi.org/10.17586/1023-5086-2020-87-06-43-50
Gerus A.V., Panova O.Yu., Savorskiĭ V.P. Modified method of orthogonal projection for object recognition in multispectral analysis [in Russian] // Opticheskii Zhurnal. 2020. Т. 87. № 6. С. 43–50. http://doi.org/10.17586/1023-5086-2020-87-06-43-50
A method for recognition of objects with undefined shapes is proposed for use in multispectral analysis. The method involves an orthogonalization procedure in an extended multidimensional spectral range along with separate utilization of information on object brightness. An optimization procedure is performed to reduce the numbers of two types of recognition errors. This method demonstrated a substantial advantage in terms of precision of recognition over the least square method, on which most recognition methods are based.
orthogonal projection, variability, extended multidimensional space, visible range, infrared range
OCIS codes: 280.4991, 280.4788, 280.4750
References:1. A. V. Gerus and T. G. Gerus, “Acousto-optical methods for identifying objects in hyperspectral analysis,” Fiz. Osn. Priborostr. 4(4), 70–83 (2015).
2. A. V. Gerus, E. V. Savchenko, and V. P. Savorskiy, “Algorithm for recognition of acoustic, optical, and electric signals from weak sources in the presence of a known background,” Zh. Radioelektron. (11) (2017).
3. A. V. Gerus, E. V. Savchenko, and V. P. Savorskiy, “Using the orthogonal projection method to identify small objects in multispectral analysis,” Sovrem. Probl. DZZ Kosm. 15(4), 27–35 (2018).
4. Afghanistan Opium Survey 2017: Cultivation and Production (United Nations Office on Drugs and Crime (UNODC) Research, Afghanistan, 2017).
5. V. P. Savorskiy, O. Yu. Panova, and E. V. Savchenko, “Methods for analyzing satellite monitoring data on plant areals to identify illegal crop fields in the conduct of special examinations,” Sovrem. Probl. DZZ Kosm. 15(5), 13–30 (2018).
6. A. V. Gerus, O. Yu. Panova, and V. P. Savorskiy, “Rapid detection of target areas of agricultural vegetation using the orthogonal projection method,” Sovrem. Probl. DZZ Kosm. 16(4), 77–85 (2019).
7. D. Manolakis and G. Shaw, “Detection algorithms for hyperspectral imaging applications,” IEEE Signal Process. Mag. 19(1), 29–43 (2002).
8. V. A. Tolpin, E. A. Lupyan, S. A. Bartalev, D. E. Plotnikov, and A. M. Matveev, “Possibilities of agricultural vegetation condition analysis with the ‘VEGA’ satellite service,” Opt. Atmos. Okeana 27(7), 581–586 (2014).
9. E. A. Loupian, A. A. Proshin, M. A. Bourtsev, I. V. Balashov, S. A. Bartalev, V. Yu. Efremov, A. V. Kashnitskiy, A. A. Mazurov, A. M. Matveev, O. A. Sydneva, I. G. Sychugov, V. A. Tolpin, and I. A. Uvarov, “IKI center for collective use of satellite data archiving, processing, and analysis systems aimed at solving the problems of environmental study and monitoring,” Sovrem. Probl. DZZ Kosm. 12(5), 263–284 (2015).