Preliminary filtering and lossy compression of noisy remote sensing images

Alexander N. Zemliachenko; Sergey K. Abramov; Vladimir V. Lukin; Benoit Vozel; Kacem Chehdi

doi:10.1117/12.2325102

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9 October 2018 Preliminary filtering and lossy compression of noisy remote sensing images

Alexander N. Zemliachenko, Sergey K. Abramov, Vladimir V. Lukin, Benoit Vozel, Kacem Chehdi

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Proceedings Volume 10789, Image and Signal Processing for Remote Sensing XXIV; 107890V (2018) https://doi.org/10.1117/12.2325102
Event: SPIE Remote Sensing, 2018, Berlin, Germany

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 prefiltering. 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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Alexander N. Zemliachenko, Sergey K. Abramov, Vladimir V. Lukin, Benoit Vozel, and Kacem Chehdi "Preliminary filtering and lossy compression of noisy remote sensing images", Proc. SPIE 10789, Image and Signal Processing for Remote Sensing XXIV, 107890V (9 October 2018); https://doi.org/10.1117/12.2325102

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