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Communication Dans Un Congrès Année : 2020

Atomic wavelets in lossy and near-lossless image compression

Résumé

One of distinguishing features of the present is the explosive increase in data amount including digital images such as satellite remote sensing images. Processing, storing and transmission via networks of a huge number of digital images requires considerable resources in the sense of memory, time, computational power, etc. In this regard, the importance of image compression is growing and the development of novel compression techniques that would satisfy new requirements, for instance, to security and level of privacy protection continues. Atomic wavelets and their generalizations can be a useful tool for this. They are constructed using atomic functions, which are compactly supported solutions of special functional differential equations. Discrete atomic transform (DAT), which is a process of computation of expansion coefficients of the function describing the source discrete data, is applied in discrete atomic compression (DAC). DAC can be applied to compression of full color digital images, as well as monocomponent ones. In this paper, we investigate efficiency, which is measured by compression ratio (CR), of satellite image compression using DAC and the corresponding loss of quality measured by several quantitative criteria. They are maximum absolute deviation (MAD), root mean square (RMS) and peak signal-to-noise ratio (PSNR). We show that DAC provides near lossless compression, when quality loss is minor in a sense of the MAD-metric. Also, it is proved that using DAC it is possible to obtain better compression than by applying JPEG with the same quality of the obtained results. © SPIE. Downloading of the abstract is permitted for personal use only.
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Dates et versions

hal-03003491 , version 1 (13-11-2020)

Identifiants

Citer

V.O. Makarichev, V.V. Lukin, I.V. Brysina, B. Vozel, K. Chehdi. Atomic wavelets in lossy and near-lossless image compression. Image and Signal Processing for Remote Sensing XXVI 2020, Sep 2020, Edinburgh, United Kingdom. pp.1153313, ⟨10.1117/12.2573970⟩. ⟨hal-03003491⟩
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