Venµs geometric image quality commissioning

Binet, Renaud; Lussy, F. de; Languille, F.; Rolland, A.; Gamet, Philippe; Raynaud, Jean-Louis; Specht, Bernard

doi:10.1117/12.2325360

Cited by 6 publications

(7 citation statements)

References 1 publication

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“…It will be updated soon for water vapour band B12. A reprocessing is scheduled at the end of 2018 with an updated configuration, bringing an enhanced geometric performance [4] and a fine radiometric calibration for B12.…”

Section: Discussionmentioning

confidence: 99%

Measuring, modeling and removing optical straylight from venμs super spectral camera images

Gamet¹,

Fourest²,

Sprecher³

et al. 2019

International Conference on Space Optics — ICSO 2018

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The Venμs Super Spectral Camera suffers from high level of optical straylight. The probable causes of this defect will be discussed. Two types of straylight are observed: local ghost is caused by scattering of optical surfaces of the instrument, and multiple reflexions between detector and filter or filter window, or lenses. Cross-talk ghost is constituted of light going through the filter of one band, and impacting another band on the same detector. It is caused by multiple reflexions between detectors and filter.The optical set-up used to evaluate the straylight patterns will be presented, and then, the approach used to characterize and model the observed phenomena will be detailed:Local straylight model is computed as a global system MTF that includes the local straylight. The assumption is made that the phenomenon can be modeled by a convolution, and that it is slowly variable within the instrument field of view. Crosstalk straylight is modeled from a pinhole, used to extract the impulsive response of the cross-talk. The cross-talk pattern is observed through the ghost generated by a saturated input signal. The cross-talk signals for all contributing bands of the same tri-detector are substracted from the image of each band.The performances of the correction model are presented: on the ground over test pattern images, and then in-flight during the image quality commissioning phase, over specific targets: moon, sand/water transitions.

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Section: Discussionmentioning

confidence: 99%

Measuring, modeling and removing optical straylight from venμs super spectral camera images

Gamet¹,

Fourest²,

Sprecher³

et al. 2019

International Conference on Space Optics — ICSO 2018

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“…Because this noise changes from one acquisition to another, it has also an impact on the multi-temporal registration quality. In-orbit calibration of the pixel's line of sight was also a challenge (Binet, 2018).…”

Section: Venμs Attitude Error and Its Consequences On Image Qualitymentioning

confidence: 99%

“…Dealing with actual attitude errors, the best economic solution was to increase the order of the polynomials up to degree 5. (Binet, 2018) describes in details the whole process and results. After all, this kind of attitude correction do benefit to the overall image geometric quality: Venµs images fullfill the registration requirements for more than 80% of all distributed images.…”

Section: Actual Geometric Corrections Of Venµs Productsmentioning

confidence: 99%

“…The satellite experiences attitude restitution errors which hampers the geometric image quality. A ground correction method has been setup by CNES at the end of in-orbit calibration campaign (Binet, 2018) and this study deals with a drastic enhancement of the geometric correction, opening new fields of applications.…”

Section: Introductionmentioning

confidence: 99%

“…Some works have already been done on the topic of Venµs attitude correction using space triangulation technique. Polynomial functions were used to estimate the attitude errors thanks to ground control points (GCPs) taken automatically on a reference image (Binet, 2018). This correction is operated systematically at the Venµs ground segment.…”

Section: Introductionmentioning

confidence: 99%

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Attitude Restitution for Multispectral Earth Observation Satellite Using Space Triangulation Technique

Baresi

Binet

Vidal

2020

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Earth observation satellites are equipped with navigation components (star trackers, gyroscopes) which estimates the attitude of the satellite, corresponding to its orientation in the orbital reference frame. This equipment is essential for the localisation of the images which is done a posteriori and for the registration of the different images for a pushbroom sensor. This concerns both the registration of the spectral bands and the registration of multi-temporal series. However, the required accuracy is not always compatible with the performance of the attitude restitution. Moreover, some specific applications need more stringent geometric control even if requirements are met. With a multi-spectral pushbroom instrument, the same object on ground is seen as many times as number of spectral bands at different time instants: the attitude profile of the platform can be completely reconstructed from the results of the mapping of the different spectral bands. An attitude reconstruction method is proposed based on space triangulation inversion technique. The framework of this study is low-frequencies noise perturbations applied to Venμs satellite. Cubic splines are used for the attitude error profile, with 60 free parameters. Provided the physical model is representative, we show on two test cases that the convergence is very good. The band registration quality is used as a proxy to assess the performances. Residuals errors are less than 0.05 pixel for all tested band couples.

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