Progressive wavelet algorithm versus JPEG for the compression of METEOSAT data

Marc P. J. Acheroy; J.-M. Mangen; Yves Buhler

doi:10.1117/12.217436

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22 August 1995 Progressive wavelet algorithm versus JPEG for the compression of METEOSAT data

Marc P. J. Acheroy, J.-M. Mangen, Yves Buhler

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Proceedings Volume 2564, Applications of Digital Image Processing XVIII; (1995) https://doi.org/10.1117/12.217436
Event: SPIE's 1995 International Symposium on Optical Science, Engineering, and Instrumentation, 1995, San Diego, CA, United States

Abstract

It is clear that the compression of Meteosat radiometric data is not a classical problem. A first challenge consists in image coding with the intention to preserve the quality of measurements. This is quite different from image coding with the intention to preserve the visual quality. The latter problem is extensively addressed in the literature. The way in which the problem of the errors is addressed is quite different in the two approaches. When the visual quality is concerned, visual criteria are used and the error amplitude can be very large in some places. On the other hand, if the measured features are extracted from radiometric data like meteorological images, it is necessary that the reconstruction errors do not exceed some threshold depending on the required precision. A second challenge concerns the construction of progressive coding scheme which allows the progressive transmission of the image data, avoiding the artifacts of a block coding scheme. In the present work, only the measurement data compression problem has been considered and the tests were realized accordingly. However, these methods also perform quite well when the visual quality is addressed. This paper presents a progressive the incoming data in the scanning order. The comparison with the JPEG standard shows that the progressive wavelet method always performs better when the distortion is concerned.

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Marc P. J. Acheroy, J.-M. Mangen, and Yves Buhler "Progressive wavelet algorithm versus JPEG for the compression of METEOSAT data", Proc. SPIE 2564, Applications of Digital Image Processing XVIII, (22 August 1995); https://doi.org/10.1117/12.217436

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