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Pre-requisites for smart lossy compression of noisy remote sensing images

Research output: Contribution to journalArticleScientificpeer-review


Original languageEnglish
Pages (from-to)225-241
Number of pages17
JournalTelecommunications and Radio Engineering
Issue number3
Publication statusPublished - 2018
Publication typeA1 Journal article-refereed


Remote sensing images are usually subject to compression for their further transmission, storage and dissemination. Because of lossy nature of compression, resulting images appear distorted. Degradations of image quality due to compression depend on noisy input image, a type and intensity of noise, and used image coder. To control image degradations, for a given coder, one should predict compression performance to be able to properly choose coder parameter(s). In this paper, we present pre-requisites for such a controlled lossy compression of noisy remote sensing images. The main attention is paid to image coders which are based on discrete cosine transform, due to relatively simple adaptation of its main parameter, quantization step, for controlling the effect of compression.

ASJC Scopus subject areas


  • Image coding, Lossy compression, Noisy image, Remote sensing

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