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Definition and Validation of Scientific Algorithms for the SEOSAT/Ingenio GPP

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Presentation by Eduardo de Miguel, Raúl Valenzuela, Teodoro Bernardino, Verena Rodríguez, Alberto Pizarro, Diana de Miguel and Severino Fernández from INTA, GMV and EADS-CASA made on Esri European ...

Presentation by Eduardo de Miguel, Raúl Valenzuela, Teodoro Bernardino, Verena Rodríguez, Alberto Pizarro, Diana de Miguel and Severino Fernández from INTA, GMV and EADS-CASA made on Esri European User Conference 2011.

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Definition and Validation of Scientific Algorithms for the SEOSAT/Ingenio GPP Presentation Transcript

  • 1. Definition and validation of scientific algorithms for the SEOSAT/Ingenio GPP Eduardo de Miguel1, Raúl Valenzuela2, Teodoro Bernardino2, Verena Rodríguez2, Alberto Pizarro3, Diana de Miguel3 , Severino Fernández11 Área de Teledetección, INTA. Cta. de Ajalvir s/n. 28850 Torrejón de Ardoz, Madrid (España). Correoelectrónico: demiguel@inta.es2 GMV Aerospace and Defence, S.A.U. C/ Isaac Newton, 11. P.T.M. Tres Cantos, 28760 Madrid(España).3 EADS-CASA Espacio. Avenida de Aragón 404, 28022, Madrid (España). Definition and validation of scientific algorithms for SEOSAT/Ingenio GPP ESRI users conference, Madrid, Sept. 2011
  • 2. Background (I)In the framework of the Spanish Earth Observation mission Ingenio, aGround Processor Prototype is being developed by GMV under contractwith EADS-CASA Espacio.This GPP is part of an end-to-end mission simulator, aimed to: 1) be used for mission performance analysis during development and verification phases, 2) be the basis for the future operational L1 ground processor, to be implemented within the Payload Data Ground Segment.Área de Teledetección - INTA supports GMV in the definition of the GPPscientific algorithms and is responsible for their validation. Definition and validation of scientific algorithms for SEOSAT/Ingenio GPP ESRI users conference, Madrid, Sept. 2011
  • 3. Background (II): Main characteristics of IngenioSun-synchronous orbit, 678 km, repetition cycle 49 days.Twin cameras, FOV ≈2.5º each; total swath 55 km.4 bands VNIR 10 m GSD; 1 pan band from 0.6 to 0.8 µm, 2.5 m GSD.Panchromatic band uses a 7 stages TDI.minimum MTF@Nyquist = 0.11 (PAN).Spectral separation with filters.Pointing accuracy: Along track 500 m Across track 100 mOnboard pre-processing: equalization and dark signal removal.Lossy compression applied to scientific TM. Definition and validation of scientific algorithms for SEOSAT/Ingenio GPP ESRI users conference, Madrid, Sept. 2011
  • 4. Background (III) The GPP includes the following tasks within the SEOSat/Ingenio L1 processingchain: •identification of saturated and bad pixels, •radiometric correction and calibration, •image restoration (denoising and deconvolution), initially only for Pan band (TBC), •geolocation and estimation of Rational Polynomial Coefficients (RPCs), •basic image classification (land / sea / bright), •quicklooks generation. Definition and validation of scientific algorithms for SEOSAT/Ingenio GPP ESRI users conference, Madrid, Sept. 2011
  • 5. L1b processing: denoisingThe algorithm selected is based on wavelet transform thresholding.Why wavelets?1) Noise is white (= equal power for all spatial frequencies),2) Noise level is known a priori:-instrumental noise from system characterization and in orbit test-photon noise from the signal level at each point3) Limitations in other noise-removal methods (median filter, FourierTransform...) Definition and validation of scientific algorithms for SEOSAT/Ingenio GPP ESRI users conference, Madrid, Sept. 2011
  • 6. L1b processing: denoisingAlgorithm configuration. •nominal wavelet basis: symlet order 4 •up to 5 decomposition levels •noise estimation at each level from the expected instrumental and photonic noise (3sigma): Noise (i,j) = 3 * sqrt(DarkN*DarkN + PhotoGain*DC(i,j)) DarkN: the instrumental noise in digital counts PhotoG: the number of photons mapped into a digital count • 75% shrinkage of those coeff<noise • proportional reduction of the other coefficients (soft thresholding) Important: noise estimation based on theoretical values for DarkN y PhotoG. Definition and validation of scientific algorithms for SEOSAT/Ingenio GPP ESRI users conference, Madrid, Sept. 2011
  • 7. Denoising validationThe first step has been building a rigorous model of systemsignal and noise for each spectral band.This model has been applied to a synthetic scene and to aairborne image acquired and processed by INTA. Lref Lmin Lmax Definition and validation of scientific algorithms for SEOSAT/Ingenio GPP ESRI users conference, Madrid, Sept. 2011
  • 8. Denoising results Nominal case Definition and validation of scientific algorithms for SEOSAT/Ingenio GPP ESRI users conference, Madrid, Sept. 2011
  • 9. Denoising results PhotoGain effect Results on natural scene Definition and validation of scientific algorithms for SEOSAT/Ingenio GPP ESRI users conference, Madrid, Sept. 2011
  • 10. L1b processing: deconvolutionInverse filtering using a specific kernel.The kernel is derived by inverting the expected instrument PSF.This procedure is a Wienerfiltering if noise is negligible.The expected PSF is an input => must be evaluated continuouisly during themission Definition and validation of scientific algorithms for SEOSAT/Ingenio GPP ESRI users conference, Madrid, Sept. 2011
  • 11. Deconvolution validationThe validation is based on analysis on the results over a syntheticscene and a natural scene.The synthetic scene is a bar pattern with spatial frequency 0.5cycles/pixel. The scene is convolved with the expected Ingenio PSFand noise is added. Next, denoising and deconvolution are applied andthe final contrast is tested:SW/SSD <1.1 after denoising and deconvolution => MTF@Nyquist >0.35.On the natural scene the procedure is similar, but we look for artifactsand not for a quantitative contrast verification. Definition and validation of scientific algorithms for SEOSAT/Ingenio GPP ESRI users conference, Madrid, Sept. 2011
  • 12. Deconvolution results Definition and validation of scientific algorithms for SEOSAT/Ingenio GPP ESRI users conference, Madrid, Sept. 2011
  • 13. Deconvolution resultsImagen AHS original Imagen degradada Min: -79 Wiener Max: 82 Media: 0.117 Diff rest - original Desvstd: 1.793 Definition and validation of scientific algorithms for SEOSAT/Ingenio GPP ESRI users conference, Madrid, Sept. 2011
  • 14. Geolocation (I)The geolocation procedure is challenging due to: -the accuracy goal requires the use of GCPs, -focal plane with different detectors, each one with a different line of sight along-track. Definition and validation of scientific algorithms for SEOSAT/Ingenio GPP ESRI users conference, Madrid, Sept. 2011
  • 15. Geolocation (IIa) Overview of the geolocation procedure-Filtering of raw AOCS data to reduce noise.-Initial geolocation using a rigorous instrument model and the filtered AOCS info.- Automatic selection of GCPs on a reference image (GMV tool) for: -estimation of thermoelastic bias -estimation of roll and pitch AOCS error per image line by fitting the errors per GCP to a continuous curve.-Fine-tunned geolocation using the bias and roll-pitch corrections. Definition and validation of scientific algorithms for SEOSAT/Ingenio GPP ESRI users conference, Madrid, Sept. 2011
  • 16. Geolocation (IIb)Overview of the geolocation procedure (cont.)Resample of the geolocated pixels on a UTM grid:-sampling interval 2.5 m / 10 m-inverse geolocation using High-order B-spline resampling.Simultaneously, a "perfect sensor" image (Pleiades way) will be produced.RPCs will be produced for this product. Definition and validation of scientific algorithms for SEOSAT/Ingenio GPP ESRI users conference, Madrid, Sept. 2011
  • 17. Geolocation (III) Geolocation validation: which is the requirement?The algorithms in the GPP shall allow the geo-location accuracy of L1b datawrt the reference ellipsoid to be better than 50 m at 2σ without GCPs.The GPP shall allow the geo-location accuracy of L1c data wrt a referencemap to be ≤ 2.5 m at 1σ with the use of < 20 GCPsThe sum of the errors due to implementation of the GPP algorithms for thegeolocation at level 1C with GCP should be less than 0.1 pixels RMS (0.3pixels, max. value). Definition and validation of scientific algorithms for SEOSAT/Ingenio GPP ESRI users conference, Madrid, Sept. 2011
  • 18. Geolocation (IV)Geolocation ValidationThe geolocation algorithm is validated using an independent geolocationmodel developed at INTA. This is based in the ESA Earth Explorer Clibraries (http://earth.esa.int/cfi/)The geolocation adjustment with the use of GCPs has been validated intwo steps:-capability to detect enough valid GCPs.=> Test passed for nominal situations (the deformation between the rawand reference images is limited, no clouds nor water bodies...).-capability to adjust roll and pitch errors from GCPs offsets=> Test passed for nominal scenes, and excluding "extrapolation"segments at the scene borders. Definition and validation of scientific algorithms for SEOSAT/Ingenio GPP ESRI users conference, Madrid, Sept. 2011
  • 19. Geolocation (Va)EEtool vs GPP (initial result) Definition and validation of scientific algorithms for SEOSAT/Ingenio GPP ESRI users conference, Madrid, Sept. 2011
  • 20. Geolocation (Vb)RMS error for a complete Ingenio scene vs number of GCPs Definition and validation of scientific algorithms for SEOSAT/Ingenio GPP ESRI users conference, Madrid, Sept. 2011
  • 21. ConclusionsThe validation of image restorarion algorithms confirms they are suitablefor the mission. Moreover, they are robust against uncertainties in theparameters involved in the image generation (PSF, DarkNoise,PhotoGain...)The algorithms selected for image geolocation achieve the requiredaccuracy in nominal conditions.The validation of the scientific algorithms for different scenarios andincluding non-nominal conditions is a challenging task. The definition, implementation and validation of the GPP algorithms is a joint work from by many engineers at GMV, EADS CASA Espacio, Astrium SAS and INTA, with the continuous support of ESA Ingenio project office and CDTI and IMAG (Ingenio Mission Advisory Group). Definition and validation of scientific algorithms for SEOSAT/Ingenio GPP ESRI users conference, Madrid, Sept. 2011
  • 22. Definition and validation of scientificalgorithms for SEOSAT/Ingenio GPPESRI users conference, Madrid, Sept. 2011