Adaptive multidimensional probabilistic transformation for multispectral digital aerospace images
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| 1Stankevich, SA, 2Sholonik, OV 1State institution «Scientific Centre for Aerospace Research of the Earth of the Institute of Geological Sciences of the National Academy of Sciences of Ukraine», Kyiv, Ukraine 2State institution «Scientific Centre for Aerospace Research of the Earth of the Institute of Geological Sciences of the National Academy of Sciences of Ukraine», Kyiv, Ukraine |
| Kosm. nauka tehnol. 2007, 13 ;(Supplement1):011-014 |
| https://doi.org/10.15407/knit2007.01s.011 |
| Publication Language: Russian |
Abstract: Adaptive multidimensional probabilistic transformation (AMPT) for multispectral and hyperspectral digital aerospace images is offered. This transformation realizes realized spectral bands optimal selection for every analyzing pixel of digital image. AMPT allows one to evaluate equivalent modulation transfer functions of multispectral digital aerospace images with higher accuracy and, hence, to provide higher equivalent spatial resolution of multispectral and hyperspectral aerospace imagery.
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| Keywords: aerospace images, modulation, spatial resolution |
References:
1. Voloshyn V. I., Korchinski V. M., Negoda O. O. Enhancement of informativeness of panchromatic space digital images. Kosm. nauka tehnol., 10 (5-6), 178—181 (2004) [in Russian].
2. Remote sensing of the Earth from space. Terms and definitions: Derzhavnyj standart Ukrai'ny DSTU 4220-2003, 18 p. (Derzhspozhyvstandart Ukrai'ny, Kyiv, 2003) [in Ukrainian].
3. Lyalko V. I., Popov M. I., Podorvan V. N., Sakhatsky A. I. The method of classification of area objects on many-spectral cosmic images on the basis of sequential merging of information. In: Current problems in remote sensing of the Earth from space: Physical basics, methods and monitoring technologies of an environment, potentially of dangerous phenomena and objects: Proceedings, Vol. 1, 88—94 (IKI RAN, Moscow, 2005) [in Russian].
4. Stankevich S. A. Statistical approach to determination of threshold modulation of digital aerospace images. Kosm. nauka tehnol., 11 (3-4), 81—84 (2005) [in Ukrainian].
5. Stankevych S. A. Static Aspects of the Vision of Functions Transferring Modulation of Aerocosmic and Systemic Systems with Discrete Photodetectors. In: Suchasni dosjagnennja geodezychnoi' nauky ta vyrobnyctva, Is. II, 142—147 (L'vivs'ka Politehnika, Lviv, 2005) [in Ukrainian].
6. Stankevich S. A. Probabilistic-frequency evaluation of equivalent spatial resolution for multispectral aerospace images. Kosm. nauka tehnol., 12 (2-3), 79—82 (2006) [in Ukrainian].
7. Stankevich S. A. The quantitative evaluation of the informativity of hyperspectral aerospace imagery on the solution of remote-sensing thematic tasks. Reports of the National Academy of Sciences of Ukraine, No. 10, 136—139 (2006) [in Ukrainian].
8. Stankevich S. A. Hyperspectral aerospace imagery spectral bands optimal selection in solving remote sensing thematic tasks. Kosm. nauka tehnol., 13 (2), 25—28 (2007) [in Russian].
https://doi.org/10.15407/knit2007.02.025
https://doi.org/10.15407/knit2007.02.025
9. Stankevich S. A., Shklyar S. V. Improved Algorithm of Determination of a Transition Function on the Digital Aerospace Image. Scientific Notes of Taurida National V.I. Vernadsky University, 18 (57), No. 2, 97—102 (2005) [in Ukrainian].
10. Aspinall R. J., Marcus W. A., Boardman J. W. Considerations in collecting, processing, and analyzing high spatial resolution hyperspectral data for environmental investigations. J. Geograph. Syst., No. 4, 15—29 (2002).
11. Nelson T., Wulder M., Niemann K. O. Spatial resolution implications of digitizing aerial photography for environmental applications. Imaging Sci. J., 49, 223—232 (2002).