Preliminary filtering and lossy compression of noisy remote sensing images

Alexander N. Zemliachenko Sergey K. Abramov Vladimir V. Lukin Benoit Vozel 1 Kacem Chehdi 1
1 IETR - Institut d'Electronique et de Télécommunications de Rennes
Abstract : Compression is a typical stage in processing of remote sensing images. Here we consider lossy compression of images that contain noise. Then, there are, at least, two approaches - to compress images without pre-filtering and with pre-filtering. The second approach is shown to have some advantages but only under certain conditions. Several metrics characterizing quality of compressed images are used. Main conclusions are in good agreement in cases of using different metrics. Recommendations concerning parameter selection for lossy compression with pre-filtering are given.
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Conference papers
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https://hal-univ-rennes1.archives-ouvertes.fr/hal-02018908
Contributor : Laurent Jonchère <>
Submitted on : Thursday, February 14, 2019 - 11:25:31 AM
Last modification on : Thursday, February 21, 2019 - 3:36:54 PM

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UNIV-RENNES1 | IETR | CNRS | UR1-UFR-ISTIC | IETR-SHINE | UNIV-NANTES | UNIV-RENNES | INSA-GROUPE

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Alexander N. Zemliachenko, Sergey K. Abramov, Vladimir V. Lukin, Benoit Vozel, Kacem Chehdi. Preliminary filtering and lossy compression of noisy remote sensing images. Conference on Image and Signal Processing for Remote Sensing XXIV, Sep 2018, Berlin, Germany. ⟨10.1117/12.2325102⟩. ⟨hal-02018908⟩

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