УДК: 004.932.2, 517.968

Adaptive method and algorithm for detecting low-contrast objects with an optoelectronic device

Katulev, A.N., Kolonskov, A.A., Khramichev, A.A., Yagolnikov, S.V.

Publication in Journal of Optical Technology

For Russian citation (Opticheskii Zhurnal):

Катулев А.Н., Колонсков А.А., Храмичев А.А., Ягольников С.В. Адаптивный метод и алгоритм обнаружения малоконтрастных объектов оптико-электронным средством // Оптический журнал. 2014. Т. 81. № 2. С. 29–39.

Katulev A.N., Kolonskov A.A., Khramichev A.A., Yagolnikov S.V. Adaptive method and algorithm for detecting low-contrast objects with an optoelectronic device [in Russian] // Opticheskii Zhurnal. 2014. V. 81. № 2. P. 29–39.

For citation (Journal of Optical Technology):

A. N. Katulev, A. A. Kolonskov, A. A. Khramichev, and S. V. Yagol’nikov, "Adaptive method and algorithm for detecting low-contrast objects with an optoelectronic device," Journal of Optical Technology. 81(2), 75-82 (2014). https://doi.org/10.1364/JOT.81.000075

Abstract:

This paper proposes an adaptive method of detecting objects on the image of an optoelectronic device. The method is based on reconstructing a reference signal-image and forming a statistic in the form of the maximum eigenvalue of the selective correlation matrix for making a decision concerning the detection of an object, using the Neyman–Pearson criterion. The information contained in the images recorded is used when there are no a priori data concerning the background–target situation. A block diagram of the algorithm is given, along with the results of estimating the efficiency index for detecting objects under various conditions.

Keywords:

image, reference signal, optoelectronic device, background, observation equation, detection criterion, method, algorythm

OCIS codes: 100.0100, 100.2000

References:

1. V. S. Kondrat’ev, A. F. Kotov, and L. N. Markov, Multiposition Radio-Engineering Systems (Radio i Svyaz’, Moscow, 1986).
2. V. T. Fesenko and T. Yu. Fesenko, “Automatic tracking of objects in computerized image-processing systems,” Opt. Zh. 74, No. 11, 39 (2007) [J. Opt. Technol. 74, 752 (2007)].
3. N. S. Shestov, Distinguishing Optical Signals on a Background of Random Noise (Sov. Radio, Moscow, 1967).
4. I. V. Borisova, “Segmentation and tracking of objects on a complex background,” Opt. Zh. 78, No. 5, 27 (2011) [J. Opt. Technol. 78, 305 (2011)].
5. E. A. Samoı˘lin, “Discrimination of image signals on a background of bimodal Gaussoid pulsed noise, optimal by the combined-limitation criterion,” Opt. Zh. 77, No. 4, 26 (2010) [J. Opt. Technol. 77, 245 (2010)].
6. V. I. Fedoseev, “Optimizing the signal processing of detector arrays, using the window method,” Opt. Zh. 77, No. 4, 60 (2010) [J. Opt. Technol. 77, 272 (2010)].
7. V. S. Murav’ev and S. I. Murav’ev, “Adaptive algorithm for discriminating and detecting airborne objects for autotracking systems,” in Scientific–Engineering Conference on Artificial Vision In Control Systems, Moscow, 14–16 March 2012, pp. 66–68.
8. D. A. Gurchenkov, M. V. Zhendarev, A. S. Nabatchivkov, and I. V. Yakimenko, “Method of detecting point thermal objects on a complex atmospheric background,” Matemat. Morf. Élektron. Matemat. Mediko-Biol. Zh. 11, No. 3, 1 (2012).
9. Yu. G. Sosulin and A. B. Russkin, “Fractal detection of extended low-contrast objects on an image,” Radiotekh. No. 12, 48 (2009).
10. A. Yilmaz, K. Shafique, and M. Shah, “Target tracking in airborne forward-looking infrared imagery,” Image Vis. Comput. 21 No. 7, 623 (2003).
11. V. S. Pugachev, Theory of Random Functions and Its Application to Problems of Automatic Control (Fizmatgiz, Moscow, 1960).
12. J. Feder, Fractals (Plenum Press, New York, 1988; Mir, Moscow, 1991).
13. A. A. Potapov, Fractals in Radiophysics and Radar (Logos, Moscow, 2002).
14. M. A. Lavrent’ev and B. V. Shabat, Methods of the Theory of Functions of a Complex Variable (Nauka, Moscow, 1973).
15. A. N. Katulev, A. A. Khramichev, and S. V. Yagol’nikov, “Fractal–statistical method of detecting objects on a two-dimensional image,” Radiotekhnika No. 11, 85 (2012).
16. B. R. Levin, Theoretical Principles of Statistical Radio Engineering. Second Book (Sov. Radio, Moscow, 1975).
17. A. E. Basharinov and B. S. Fleı˘shman, Methods of Statistical Sequential Analysis and Their Radio-Engineering Applications (Sovetskoe Radio, Moscow, 1962), pp. 230–241.
18. A. N. Katulev, A. N. Kudinov, M. A. Malevinskiı˘, and G. M. Solomakha, “Integral operator for differentiating two-dimensional random fields,” Radioteknika No. 14, 15 (2008).