Discrete atomic compression of satellite images: a comprehensive efficiency research

Viktor O. Makarichev; Vladimir V. Lukin; Iryna V. Brysina; Benoit Vozel; Kacem Chehdi

doi:10.1117/12.2599895

12 September 2021 Discrete atomic compression of satellite images: a comprehensive efficiency research

Viktor O. Makarichev, Vladimir V. Lukin, Iryna V. Brysina, Benoit Vozel, Kacem Chehdi

Proceedings Volume 11862, Image and Signal Processing for Remote Sensing XXVII; 118620Q (2021) https://doi.org/10.1117/12.2599895
Event: SPIE Remote Sensing, 2021, Online Only

Abstract

In this paper, a problem of resource expenses needed for storage, processing and transferring a large number of high resolution digital remote sensing images is considered. Application of discrete atomic compression (DAC), which is an algorithm based on atomic wavelets, to solving this problem is studied. Dependence of efficiency of the DAC algorithm on its parameters, in particular, quality loss settings, a structure of discrete atomic transform, which is a core of DAC, and a method of quantized wavelet coefficients’ encoding, is investigated. Binary arithmetic coding and a combination of Huffman codes with run-length encoding are used to provide lossless compression of quantized atomic wavelet coefficients. Comparison of these methods is presented. A set of digital images of the European Space Agency is employed as test data. In addition, we discuss promising ways to improve the DAC algorithm.

Conference Presentation

Citation Download Citation

Viktor O. Makarichev, Vladimir V. Lukin, Iryna V. Brysina, Benoit Vozel, and Kacem Chehdi "Discrete atomic compression of satellite images: a comprehensive efficiency research", Proc. SPIE 11862, Image and Signal Processing for Remote Sensing XXVII, 118620Q (12 September 2021); https://doi.org/10.1117/12.2599895

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