doi: 10.17586/2226-1494-2018-18-4-573-580


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. A method of images contrast enhancement under conditions of the Earth survey from space. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2018, vol. 18, no. 4, pp. 573–580 (in Russian). doi: 10.17586/2226-1494-2018-18-4-573-580


Subject of Research. A method is proposed for the contrast enhancement of the Earth's surface images  obtained by airborne optoelectronic complexes of space remote sensing systems. The relevance of the proposed method is confirmed by the results of contrast estimation  for space images obtained by modern recording equipment and the results of the contrast calculation for modeled survey conditions. Method. The method is based on the idea of combining different exposure space images. This combination gives the possibility to get the resulting snapshot with an extended dynamic range of brightness. Such picture has a high contrast in the field of dark and light halftones and displays the details of the observed objects better. Main Results. The contrast of the image obtained when selecting the survey parameters by traditional method is estimated. It is concluded that the quality of the images obtained from space is currently limited, since the parameters of the onboard optoelectronic complex do not provide taking into account a larger number of objects with different optical characteristics that are within the capture area of the recording equipment. On the basis of research, an approach to images contrast enhancement is proposed, the essence of which is to expand the dynamic range of brightness and, as a result, to increase the contrast of the images obtained. Practical Relevance. The proposed method for the Earth's remote sensing data processing gives the possibility to obtain images of objects located on the Earth's surface in any light conditions suitable for interpretation. This fact will improve the accuracy of information provision when performing work survey support and mapping areas

Keywords: combining images, exposure, image brightness dynamic range, space image quality, contrast

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.     ZaninK.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., 2014, 234 p.
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, 2017, 104 p. (in Russian)

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.