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Editor-in-Chief
Nikiforov
Vladimir O.
D.Sc., Prof.
Partners
doi: 10.17586/2226-1494-2015-15-4-595-602
METHOD OF RADIOMETRIC DISTORTION CORRECTION OF MULTISPECTRAL DATA FOR THE EARTH REMOTE SENSING
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Article in Russian
For citation: Grigoriev А.N. Мethod of radiometric distortion correction of multispectral data for the earth remote sensing. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2015, vol.15, no. 4, pp. 595–602.
Abstract
For citation: Grigoriev А.N. Мethod of radiometric distortion correction of multispectral data for the earth remote sensing. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2015, vol.15, no. 4, pp. 595–602.
Abstract
The paper deals with technologies of ground secondary processing of heterogeneous multispectral data. The factors of heterogeneous data include uneven illumination of objects on the Earth surface caused by different properties of the relief. A procedure for the image restoration of spectral channels by means of terrain distortion compensation is developed. The object matter of this paper is to improve the quality of the results during image restoration of areas with large and medium landforms. Methods. Researches are based on the elements of the digital image processing theory, statistical processing of the observation results and the theory of multi-dimensional arrays. Main Results. The author has introduced operations on multidimensional arrays: concatenation and elementwise division. Extended model description for input data about the area is given. The model contains all necessary data for image restoration. Correction method for multispectral data radiometric distortions of the Earth remote sensing has been developed. The method consists of two phases: construction of empirical dependences for spectral reflectance on the relief properties and restoration of spectral images according to semiempirical data. Practical Relevance. Research novelty lies in development of the application theory of multidimensional arrays with respect to the processing of multispectral data, together with data on the topography and terrain objects. The results are usable for development of radiometric data correction tools. Processing is performed on the basis of a digital terrain model without carrying out ground works connected with research of the objects reflective properties.
Keywords: data processing, radiometric correction, data model, digital terrain model, multidimensional array, concatenation, empirical
dependence.
References
References
1. Grigor'ev A.N. Perspektivy vozdushno-kosmicheskogo monitoringa s ispol'zovaniem sredstv giperspektral'noi s"emki [Prospects for aerospace monitoring with the use of hyperspectral survey]. Sbornik Trudov I Vserossiiskoi Konferentsii Molodykh Uchenykh Nauka i Innovatsii XXI Veka [Proc. All-Russian Conference of Young Scientists Science and Innovation XXI Century]. Surgut, Russia, 2012, pp. 15–19.
2. Grigor'ev A.N. Issledovanie topograficheskikh radiometricheskikh iskazhenii dannykh kosmicheskoi giperspektral'noi s"emki [Research of topographic data radiometric distortion of space hyperspectral survey]. Kontenant, 2013, vol. 12, no. 1, pp. 50–57.
3. Grigor'ev A.N., Shilin B.V. Analysis of seasonal variations of the spectral characteristics of landscape components, using the data of the Hyperion space video spectrometer. Journal of Optical Technology (A Translation of Opticheskii Zhurnal), 2013, vol. 80, no. 6, pp. 360–362. doi: 10.1364/JOT.80.000360
4. Vicente-Serrano S., Perez-Cabello F., Lasanta T. Assessment of radiometric correction techniques in analyzing vegetation variability and change using time series of Landsat images. Remote Sensing of Environment, 2008, vol. 112, no. 10, pp. 3916–3934. doi: 10.1016/j.rse.2008.06.011.
5. Grigoriev A.N. The method of formation of objects spectral characteristics on the basis of multitemporal data of space hyperspectral remote sensing. Sovremennye Problemy Distantsionnogo Zondirovaniya Zemli iz Kosmosa, 2014, vol. 11, no. 2, pp. 175–184. (in Russian)
6. Richter R., Kellenberger T., Kaufmann H. Comparison of topographic correction methods. Remote Sensing, 2009, vol. 1, no. 3, pp. 184–196. doi: 10.3390/rs1030184.
7. Liu C., Li N., Li X., Zhao H. The research by topographic correction methods of airborne hyperspectral remote sensing data based on DEM. Proceedings of SPIE – The International Society for Optical Engineering, 2014, vol. 9260, art. 926049. doi: 10.1117/12.2069395.
8. Vanonckelen S., Lhermitte S., Balthazar V., Van Rompaey A. Performance of atmospheric and topographic correction methods on Landsat imagery in mountain areas. International Journal of Remote Sensing, 2014, vol. 35, no. 13, pp. 4952–4972. doi: 10.1080/01431161.2014.933280.
9. Gao Y., Zhang W. A simple empirical topographic correction method for ETM+ imagery. International Journal of Remote Sensing, 2009, vol. 30, no. 9, pp. 2259–2275. doi: 10.1080/01431160802549336
10. Wang L., Wang Q. A new semi-empirical topographic correction method for optical remote sensing imagery in rugged terrain. Proc. SPIE Proceedings of SPIE – The International Society for Optical Engineering, 2010, vol. 7841, art. 784108. doi: 10.1117/12.873155
11. Zhang W., Gaob Y. Topographic correction algorithm for remotely sensed data accounting for indirect irradiance. International Journal of Remote Sensing, 2011, vol. 32, no. 7, pp. 1807–1824. doi: 10.1080/01431161003623441.
12. Lenot X., Achard V., Poutier L. A new approach to atmospheric and topographic corrections for hyperspectral imagery. Remote Sensing of Environment, 2009, vol. 113, no. 8, pp. 1664–1677. doi: 10.1016/j.rse.2009.03.016.
13. Markov A.V., Grigor'eva O.V., Chapurskii L.I., Mochalov V.F. Metody podgotovki etalonnoi informatsii dlya obrabotki materialov mnogo- i giperspektral'noi aerokosmicheskoi s"emki v zadache monitoringa prirodnoi sredy [Methods of preparing standard information for multi-material processing and hyperspectral aerospace shooting in the problem of environmental monitoring]. Trudy III Vserossiiskoi Nauchnoi Konferentsii "Problemy Voenno-Prikladnoi Geofiziki i Kontrolya Sostoyaniya Prirodnoi Sredy" [Proc. III All-Russian Scientific Conference "Problems of Military-Applied Geophysics and Environmental Control"]. St. Petersburg, 2014, vol. 2, pp. 324–332.
14. Grigor'ev A.N. Metod sokrashcheniya izbytochnosti giperspektral'nykh dannykh distantsionnogo zondirovanii Zemli [The method of reducing redundancy of hyperspectral remote sensing data]. Raketno-Kosmicheskoe Priborostroenie i Informatsionnye Tekhnologii, 2012, pp. 69–77.
15. Titkov B.V., Shabakov E.I. Operator lineinoi fil'tratsii ob"emnogo izobrazheniya v imitatsionnom modelirovanii televizionnoi sistemy [The operator of linear filtering in 3D image simulation television system]. Tekhnika Sredstv Svyazi, 1984, no. 2, pp. 69–76.