Discrete Atomic Transform-Based Lossy Compression of Three-Channel Remote Sensing Images with Quality Control

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dc.contributor.authorMakarichev, Victor
dc.contributor.authorVasilyeva, Irina
dc.contributor.authorLukin, Vladimir
dc.contributor.authorVozel, Benoit
dc.contributor.authorShelestov, Andrii
dc.contributor.authorKussul, Nataliia
dc.date.accessioned2022-07-12T14:09:44Z
dc.date.available2022-07-12T14:09:44Z
dc.date.issued2021
dc.description.abstractenLossy compression of remote sensing data has found numerous applications. Several requirements are usually imposed on methods and algorithms to be used. A large compression ratio has to be provided, introduced distortions should not lead to sufficient reduction of classification accuracy, compression has to be realized quickly enough, etc. An additional requirement could be to provide privacy of compressed data. In this paper, we show that these requirements can be easily and effectively realized by compression based on discrete atomic transform (DAT). Three-channel remote sensing (RS) images that are part of multispectral data are used as examples. It is demonstrated that the quality of images compressed by DAT can be varied and controlled by setting maximal absolute deviation. This parameter also strictly relates to more traditional metrics as root mean square error (RMSE) and peak signal-to-noise ratio (PSNR) that can be controlled. It is also shown that there are several variants of DAT having different depths. Their performances are compared from different viewpoints, and the recommendations of transform depth are given. Effects of lossy compression on three-channel image classification using the maximum likelihood (ML) approach are studied. It is shown that the total probability of correct classification remains almost the same for a wide range of distortions introduced by lossy compression, although some variations of correct classification probabilities take place for particular classes depending on peculiarities of feature distributions. Experiments are carried out for multispectral Sentinel images of different complexities.uk
dc.format.pagerangeP. 1-35uk
dc.identifier.citationDiscrete Atomic Transform-Based Lossy Compression of Three-Channel Remote Sensing Images with Quality Control / Makarichev V., Vasilyeva I., Lukin V., Vozel B., Shelestov A., Kussul N. // Remote Sensing. – 2021. – 14(1), 125. – P. 1-35.uk
dc.identifier.urihttps://www.mdpi.com/2072-4292/14/1/125
dc.identifier.urihttps://ela.kpi.ua/handle/123456789/48726
dc.language.isoenuk
dc.publisherRemote Sensinguk
dc.subjectremote sensinguk
dc.subjectlossy compressionuk
dc.subjectdiscrete atomic transformuk
dc.subjectimage quality controluk
dc.subjectprivacy protectionuk
dc.subjectimage classificationuk
dc.titleDiscrete Atomic Transform-Based Lossy Compression of Three-Channel Remote Sensing Images with Quality Controluk
dc.typeArticleuk

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