On non-uniform sampling for remote sensing optical images: the METEOSAT third generation rectification case study

Rebeca Gutiérrez; Dieter Just

doi:10.1117/12.2028643

17 October 2013 On non-uniform sampling for remote sensing optical images: the METEOSAT third generation rectification case study

Rebeca Gutiérrez, Dieter Just

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Proceedings Volume 8892, Image and Signal Processing for Remote Sensing XIX; 889206 (2013) https://doi.org/10.1117/12.2028643
Event: SPIE Remote Sensing, 2013, Dresden, Germany

Abstract

The METEOSAT Third Generation (MTG) Programme will provide the geostationary platforms for operational meteorological data acquisitions over Europe in 2018-2030. The Flexible Combined Imager (FCI) instrument is one of the MTG imager instruments and has a heritage from SEVIRI flown on the current METEOSAT Second Generation (MSG) satellites. It is a radiometer providing measurements in 16 spectral bands with a full Earth coverage every 10 minutes. For the Level 2 processing of FCI datasets the measurements have to be re-sampled on a constant reference grid in a geostationary projection – this process is referred to as rectification. The use of a three-axis stabilised platform and the scanning scheme applied to the FCI make rectification in MTG more challenging than in the MSG/SEVIRI case. Classical interpolation formulas assume a uniform sampling spacing of the measurements. However, non-uniform sampling may occur in the FCI sampling acquisition due to platform dynamics, micro-vibrations, thermo-elastic focal plane and optical distortions. In such a case, classical methods can cause significant rectification errors and interpolation algorithms, which can cope with non-uniform sampling, are required. This paper analyses the effect of non-uniform sampling in the FCI rectification process and aims to select and assess suitable resampling algorithms for the FCI L1 processing chain. Several techniques tailored to non-uniform resampling have been implemented. Performances of both uniform and non-uniform interpolation algorithms have been evaluated and compared using simulated FCI-like data samples. The analysis has been done for a nominal and a worst-case sample acquisition scenario. The presentation will show the results of our simulations with respect to the MTG requirements.

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Rebeca Gutiérrez and Dieter Just "On non-uniform sampling for remote sensing optical images: the METEOSAT third generation rectification case study", Proc. SPIE 8892, Image and Signal Processing for Remote Sensing XIX, 889206 (17 October 2013); https://doi.org/10.1117/12.2028643

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KEYWORDS

Error analysis

Imaging systems

MATLAB

Reconstruction algorithms

Convolution

Image processing

Remote sensing

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