Statistical atmospheric parameter retrieval largely benefits from spatial-spectral image compression
García-Sobrino, Joaquín (Universitat Autònoma de Barcelona. Departament d'Enginyeria de la Informació i de les Comunicacions)
Serra Sagristà, Joan (Universitat Autònoma de Barcelona. Departament d'Enginyeria de la Informació i de les Comunicacions)
Laparra, Valero (Universitat de Valencia. Laboratori de Processament d'imatges)

Data:	2017
Resum:	The infrared atmospheric sounding interferometer (IASI) is flying on board of the Metop satellite series, which is part of the EUMETSAT Polar System. Products obtained from IASI data represent a significant improvement in the accuracy and quality of the measurements used for meteorological models. Notably, the IASI collects rich spectral information to derive temperature and moisture profiles, among other relevant trace gases, essential for atmospheric forecasts and for the understanding of weather. Here, we investigate the impact of near-lossless and lossy compression on IASI L1C data when statistical retrieval algorithms are later applied. We search for those compression ratios that yield a positive impact on the accuracy of the statistical retrievals. The compression techniques help reduce certain amount of noise on the original data and, at the same time, incorporate spatial-spectral feature relations in an indirect way without increasing the computational complexity. We observed that compressing images, at relatively low bit rates, improves results in predicting temperature and dew point temperature, and we advocate that some amount of compression prior to model inversion is beneficial. This research can benefit the development of current and upcoming retrieval chains in infrared sounding and hyperspectral sensors.
Ajuts:	European Commission 647423 Ministerio de Economía y Competitividad TIN2015-71126-R Ministerio de Economía y Competitividad TIN2012-38102-C03-00 Agència de Gestió d'Ajuts Universitaris i de Recerca 2014/SGR-691
Drets:	Tots els drets reservats.
Llengua:	Anglès
Document:	Article ; recerca ; Versió acceptada per publicar
Matèria:	Image coding ; Transform coding ; Transforms ; Temperature measurement ; Atmospheric measurements ; Atmospheric modeling ; Satellites
Publicat a:	IEEE transactions on geoscience and remote sensing, Vol. 55, issue 4 (April 2017) , p. 2213-2224, ISSN 1558-0644

DOI: 10.1109/TGRS.2016.2639099

Post-print 11 p, 1.3 MB

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Documents de recerca > Documents dels grups de recerca de la UAB > Centres i grups de recerca (producció científica) > Enginyeries > Group on Interactive Coding of Images (GICI)
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