Discrete Atomic Compression with Different Structures of Discrete Atomic Transform: Efficiency Comparison and Perspectives of Application to Digital Images Privacy Protection

Makarichev, Viktor; Brysina, Iryna

doi:10.1109/dessert50317.2020.9125073

Cited by 7 publications

(6 citation statements)

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“…Finally, the algorithm DAC was compared with JPEG in [40,41,47]. It has been shown that, on average, DAC provides a higher compression ratio than JPEG for the same quality measured by PSNR.…”

Section: Discussionmentioning

confidence: 99%

“…In [47], DAT1 of the depth 5 and DAT2 of the depth 5 were considered, and it was shown that they provided almost the same compression ratio with the same distortions measured by RMSE (actually, only one compression mode of DAC, which provides the average RMSE = 2.8913, was considered), i.e., a significant variation of DAT structure does not reduce the efficiency of the DAC. It was proposed to apply this feature in order to provide protection of digital images.…”

Section: Discrete Atomic Transformmentioning

confidence: 99%

“…Further, we compare DAT1 and DAT2. In opposite to [47], in the current research, a greater number of DAT structures is considered. Moreover, analysis is carried out for a wider range of quality loss levels.…”

Section: Discrete Atomic Transformmentioning

confidence: 99%

“…(2) is it possible to reconstruct an image correctly if a lossy compression algorithm is applied? It has been recently shown that privacy of images compressed by DAT [47] can be provided practically without increasing the size of compressed files (actually, protection is integrated into compression). This is one of its obvious advantages that will be discussed in this paper in more detail.…”

Section: Introductionmentioning

confidence: 99%

“…• DAT is used as the basis of compression and we are interested in the analysis of its performance since it is rather fast, allows providing privacy of data, and has some other advantages [40,41,47,57];…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2021

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Lossy 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.

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Section: Discussionmentioning

confidence: 99%

Section: Discrete Atomic Transformmentioning

confidence: 99%

Section: Discrete Atomic Transformmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%