doi: 10.17586/2226-1494-2019-19-1-39-46


METHOD OF SPACE IMAGES QUALITY IMPROVEMENT AT EARTH-VIEWING IN WINTER PHENOLOGICAL PERIOD

A. I. Altuchov, E. I. Shabakov, D. S. Korshunov


Read the full article  ';
Article in Russian

For citation:
Altukhov A.I., Shabakov E.I., Korshunov D.S. Method of space images quality improvement at earth-viewing in winter phenological period. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2019, vol. 19, no. 1, pp. 39–46 (in Russian). doi: 10.17586/2226-1494-2019-19-1-39-46


Abstract
Subject of research. During the winter phenological period, the largest part of the solar radiation flux is reflected from the earth's surface. The reason is the presence of snow cover on the earth's surface, which has high reflectance of the radiation flux. Under these conditions, the choice of shooting modes of the Earth from space is limited. Long exposure modes cannot be selected. As a result, the pictures have low quality and their interpretation is difficult. The proposed method provides the images of the earth's surface suitable for processing in view of the space survey features in winter phenological period. The method significance is confirmed by the results of the contrast evaluation of satellite images. Method. The method is based on the idea of co-processing of a series of space images with different exposures. The result of processing is a snapshot with an extended dynamic brightness range possessing high contrast in the areas of dark and pale halftones. Such snapshot displays better the borders and details of geographic area objects and that simplifies significantly its interpretation. Main results. We analyzed the effect of space survey ballistic conditions on the results of method application for image quality improvement in winter phenological period. The conclusion was drawn that the results of joint processing of images with different exposures can be ill-posed. The cause lies in geometric distortions due to continuous relative motion of the observed area and a spacecraft. The variant to eliminate geometric distortions by camera engineering development is proposed. Practical relevance. The prossessing method for the Earth's remote sensing data provides obtaining suitable for interpretation satellite images of the objects located on the earth surface in any phenological period. The results are applicable for the information accuracy increase in survey and cartography support.

Keywords: image synthesis, image brightness dynamic range, contrast

References
1. Veselov Yu.G., Ostrovskii A.S., Sel'vesyuk N.I., Krasavin I.V. Estimation of the limiting resolution of digital optoelectronic systems of remote sensing using the theory of linear systems. Izvestiya YuFU. Tekhnicheskie Nauki, 2013, no. 3, pp. 84–89. (in Russian)
2. Grigor'ev A.N., Korshunov D.S., Belyaev A.S. Forecasting quality satellite images of space remote sensing systems. Trudy Voenno-Kosmicheskoi Akademii im. A.F. Mozhaiskogo, 2010, no. 629, pp. 143–147. (in Russian)
3. Grigoriev A.N., Dudin E.A., Korshunov D.S., Oktiabrskii V.V. The conceptual and analytical models of optoelectronic survey with prior exposure metering on board a spacecraft. Current Problems in Remote Sensing of the Earth from Space, 2017, vol. 14, no. 3, pp. 128–138. (in Russian)
4. Altukhov A.I., Gnusarev N.V., Korshunov D.S. Image quality forecasting for space objects. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2013, no. 3, pp. 36–41. (in Russian)
5. Zanin K.A. Image quality based selection of parameters of optical-electronic space observation system. Polet. Obshcherossiiskii Nauchno-Tekhnicheskii Zhurnal, 2007, no. 11, pp. 30–37. (in Russian)
6. Baklanov A.I. Observation and Monitoring Systems. Moscow, Binom Publ., 2009, 234 p. (in Russian)
7. Altukhov A.I., Korshunov D.S., Shabakov E.I. Method of image quality enhancement for space objects. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2014, no. 4, pp. 35–40. (in Russian)
8. Altuhov A.I., Shabakov E.I., Korshunov D.S. Increased image quality by synthesizing space photos with different exposures. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2017, vol. 17, no. 1, pp. 24–30. doi: 10.17586/2226-1494-2017-17-1-24-30
9. Krasil'nikov N.N. Digital Processing of 2D and 3D Images. St. Petersburg, BKhV-Peterburg Publ., 2011, 608 p. (in Russian)
10. Vasil'ev A.S., Korotaev V.V., Krasnyashchikh A.V., Lashmanov O.Yu., Nenarokomov O.N. Superposition of thermal and television images in examination of building units and constructions. Journal of Instrument Engineering, 2012, vol. 55, no. 4, pp. 12–16. (in Russian)
11. Vasil'ev A.S., Krasnyashchikh A.V., Korotaev V.V., Lashmanov O.Yu., Lysenko D.Yu., Nenarokomov O.N., Shirokov A.S., Yaryshev S.N. Unmanned aerial vehicle computer system for wildfire detection by image superimposing. Journal of Instrument Engineering, 2012, vol. 55, no. 12, pp. 50–55. (in Russian)
12. Lashmanov O.U., Vasilev A.S., Vasileva A.V., Anisimov A.G., Korotaev V.V. High-precision absolute linear encoder based on a standard calibrated scale. Measurement, 2018, vol. 123, pp. 226–234. doi: 10.1016/j.measurement.2018.03.071
13. Korotaev V.V., Mel'nikov G.S., Mikheev S.V., Samkov V.M., Soldatov Yu.I. Basics of Thermal Imaging. St. Petersburg, NRU ITMO Publ., 2012, 122 p. (in Russian)
14. Gorbachev A.A., Korotaev V.V., Yaryshev S.N. Solid-State Matrix Photoconverters and Cameras Based on Them. St. Petersburg, NRU ITMO Publ., 2013, 98 p. (in Russian)
15. Korotaev V.V., Maraev A.A. Sources and Detectors of Optical Radiation. St. Petersburg, ITMO University Publ., 2017, 104 p.


Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Copyright 2001-2024 ©
Scientific and Technical Journal
of Information Technologies, Mechanics and Optics.
All rights reserved.

Яндекс.Метрика