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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, 2024, Vol. 21, No. 6, pp. 130-142

Features of LERC image compression algorithm application in Earth remote sensing data archiving

A.A Proshin 1 , E.A. Loupian 1 , M.A. Burtsev 1 
1 Space Research Institute RAS, Moscow, Russia
Accepted: 21.10.2024
DOI: 10.21046/2070-7401-2024-21-6-130-142
Recent decades have provided an almost exponential growth of remote sensing data volumes. This is due both to the increase in the number of operational, including open-access, satellite systems and to the improvement of performance of imaging systems and the growth in the number of available information products. Therefore, the search for new approaches for more efficient remote sensing data storage, including through the improvement of their compression mechanisms that allow preserving the required data quality and providing high speed access to them, including the use of lossy compression algorithms, remains one of the urgent tasks. This paper is devoted to analyzing the possibility of using the LERC (Limited Error Raster Compression) lossy compression algorithm, which allows setting the maximum error in a pixel, for compression of various types of remote sensing satellite data. The paper considers the influence of a set maximum error on both the degree of data compression and the features of introduced distortions both in the radiometric properties of the data, the level of which the algorithm allows to control, and in the spatial characteristics of the compressed images. Special focus is on the analysis of image texture distortions depending on the level of allowable error used in compression. In order to determine the maximum allowable compression error that does not lead to the loss of either radiometric or structural properties of the image, a technique based on quantitative assessment of changes observed in image texture at different levels of maximum error is proposed, and the results of application of the technique to different types of remote sensing data acquired in the visible range and products obtained from their processing are presented.
Keywords: satellite data, Earth remote sensing, satellite data archives, efficient data compression, satellite data access systems
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