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ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2020, Vol. 17, No. 5, pp. 35-44

Calculation technique of satellite imaging quality assessment criterion based on geometrical concentration calculation

E.A. Maltsev 1 , Yu.A. Maglinets 2 , R.V. Brezhnev 2 
1 Skolkovo Institute of Science and Technology, Moscow, Russia
2 Institute of Space and Information Technologies, Siberian Federal University, Krasnoyarsk, Russia
Accepted: 21.08.2020
DOI: 10.21046/2070-7401-2020-17-5-35-44
The paper considers calculation methods of an objective satellite imaging quality assessment criterion based on geometrical concentration of image defects. Areas covered with clouds are considered as defects. An objective assessment implies an automatic calculation mode without the involvement of expert groups. Calculation of the geometrical concentration of objects on the plane based on Delaunay triangulation allows to proceed to the level of relational structures analysis, taking into account the information about mutual position of the objects in the image, and moreover to assess the nature of defects positioning in the form of a cloud cover. The paper shows the advantage of the proposed criterion of satellite image quality in comparison with the assessment based on the percentage of cloudiness. This criterion can be used in satellite data catalogs when selecting data for thematic processing. Approbation of calculation methods was conducted using random sampling of satellite images; the obtained quantitative results characterize the degree of images applicability for thematic processing. Recommendations for the application of the criterion under consideration in the selection and filtering of satellite images in the tasks of agricultural monitoring are formulated.
Keywords: image processing, remote sensing, image quality assessment, geometrical concentration, cloudiness
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