Abstract
Algorithms and information technologies for processing Earth hyperspectral imagery are presented. Several new approaches are discussed. Peculiar properties of processing the hyperspectral imagery, such as multifold signal-to-noise reduction, atmospheric distortions, access to spectral characteristics of every image point, and high dimensionality of data, were studied. Different measures of similarity between individual hyperspectral image points and the effect of additive uncorrelated noise on these measures were analyzed. It was shown that these measures are substantially affected by noise, and a new measure free of this disadvantage was proposed. The problem of detecting the observed scene object boundaries, based on comparing the spectral characteristics of image points, is considered. It was shown that contours are processed much better when spectral characteristics are used instead of energy brightness. A statistical approach to the correction of atmospheric distortions, which makes it possible to solve the stated problem based on analysis of a distorted image in contrast to analytical multiparametric models, was proposed. Several algorithms used to integrate spectral zonal images with data from other survey systems, which make it possible to image observed scene objects with a higher quality, are considered. Quality characteristics of hyperspectral data processing were proposed and studied.
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References
Akhmetov, R.N. and Stratilatov, N.R., New technologies for the analysis and processing of the Earth’s remote sensing data, Aerokosmicheskii Kur’er, 2011, no. 6, pp. 22–24.
Akhmetov, R.N., Stratilatov, N.R., Yudakov, A.A., Vezenov, V.I., and Eremeev, V.V., Main directions of research on the development of technologies for processing of data from hyperspectral surveying of the Earth, Proc. of the Scientific and Technical Conf. “Hyperspectral Instrumentation and Technologies,” Moscow: JSC “Krasnogorskii zavod im. S.A. Zvereva,” 2013, pp. 23–24.
Akhmet’yanov, V.R., Nikolenko, A.A., and Terent’eva, V.V., Development of space hyperspectral instrumentation in foreign countries, Proc. of the Scientific and Technical Conf. “Hyperspectral Instrumentation and Technologies,” Moscow: JSC “Krasnogorskii zavod im. S.A. Zvereva,” 2013, pp. 41–42.
Antonushkina, S.V., Eremeev, V.V., Makarenkov, A.A., and Moskvitin, A.E., Specific features of analysis and processing of data obtained from hyperspectral surveying of the Earth’s surface, Tsifrovaya Obrabotka Signalov, 2010, no. 4, pp. 38–43.
Arkhipov, S.A., Lyakhov, A.Yu., and Tarasov, A.P., Activities of JSC “Krasnogorskii zavod im. S.A. Zvereva” on the development of hyperspectral remote sensing instruments, Proc. of the Scientific and Technical Conf. “Hyperspectral Instrumentation and Technologies,” Moscow: JSC “Krasnogorskii zavod im. S.A. Zvereva,” 2013, pp. 25–30.
Bondur, V.G., Modern approaches to processing large hyperspectral and multispectral aerospace data flows, Izv., Atmos. Ocean. Phys., 2014, vol. 50, no. 9, pp. 840–852.
Eremeev, V.V., Makarenkov, A.A., Moskvitin, A.E., and Yudakov, A.A., Improving the contrast of objects on data of hyperspectral surveying of the Earth’s surface, Tsifrovaya Obrabotka Signalov, 2012, no. 3, pp. 35–40.
Eremeev, V.V., Modern activities on the analysis and enhancement of quality of space images of the Earth’s surface, Tsifrovaya Obrabotka Signalov, 2012a, no. 1, pp. 38–44.
Eremeev, V.V., Current problems in the processing of the Earth’s remote sensing data, Radiotekhnika, 2012b, no. 3, pp. 54–64.
Gut, N., Hypercpectral imaging, Spectroscopy, 1999, vol. 14, no. 3, pp. 28–42.
Khailov, M.N. and Zaichko, V.A., Hyperspectral surveying-the prospects of its use in solving social and economic problems, Proc. of the Scientific and Technical Conf. “Hyperspectral Instrumentation and Technologies,” Moscow: JSC “Krasnogorskii zavod im. S.A. Zvereva,” 2013, pp. 10–11.
Kozoderov, V.V., Kondranin, T.V., Dmitriev, E.V., Kazantsev, O.Yu., Persev, I.V., and Shcherbakov, M.V., Processing of hyperspectral aerospace sounding data, Issled. Zemli Kosmosa, 2012, no. 5, pp. 3–11.
Mahiny, A.S. and Turner, B.J., A comparison of four common atmospheric correction methods, Photogram. Eng. Remote Sens., 2007, vol. 73, pp. 361–368.
Makarenkov, A.A. and Yudakov, A.A., Statistical correction of atmospheric distortions in hyperspectral satellite images of the Earth’s surface, Proc. of the All-Russian Scientific and Practical Conference “Current Problems of Space-Rocket Instrumentation and Information Technologies,” Moscow: JSC “Rossiiskie kosmicheskie sistemy,” 2012, pp. 54–55.
Pozhar, V.E. and Pustovoit, V.I., Possibilities for creating new vision systems on the basis of acoustic and optical video spectrometers, Radiotekh. Elektron. (Moscow), 1996, vol. 41, no. 10, pp. 1272–1278.
San, B.T. and Suzen, M.L., Evaluation of different atmospheric correction algorithms for EO-1 Hyperion imagery, International Archives of the Photogrammetry, Remote Sens. Spatial Inform. Sci., 2010, vol. 38, no. 8, pp. 392–397.
Shovengerdt, R.A., Distantsionnoe zondirovanie. Modeli i metody obrabotki izobrazhenii (Remote Sensing. Models and Methods of Image Processing), Moscow: Tekhnosfera, 2012.
Yuhas, R.H., Goetz, A.F.H., and Boardman, J.W., Discrimination among semiarid landscape endmembers using the spectral angle mapper (SAM) algorithm, Summaries 3rd Annual JPL Airborne Geosci. Workshop, JPL, 1992, vol. 1, no. 92-14, pp. 147–149.
Zlobin, V.K. and Eremeev, V.V., Obrabotka aerokosmicheskikh izobrazhenii (Aerospace Image Processing), Moscow: Fizmatlit, 2006.
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Original Russian Text © R.N. Achmetov, N.R. Stratilatov, A.A. Yudakov, V.I. Vezenov, V.V. Eremeev, 2014, published in Issledovanie Zemli iz Kosmosa, 2014, No. 1, pp. 17–28.
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Achmetov, R.N., Stratilatov, N.R., Yudakov, A.A. et al. Models of formation and some algorithms of hyperspectral image processing. Izv. Atmos. Ocean. Phys. 50, 867–877 (2014). https://doi.org/10.1134/S0001433814090023
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DOI: https://doi.org/10.1134/S0001433814090023