2016
DOI: 10.5194/isprs-archives-xli-b1-291-2016
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2D Sub-Pixel Disparity Measurement Using QPEC / Medicis

Abstract: Commission V, WG V/4KEY WORDS: 2D Stereo Matching, Sub-pixel Disparity, Geometric Calibration, QPEC, Medicis ABSTRACT:In the frame of its earth observation missions, CNES created a library called QPEC, and one of its launcher called Medicis. QPEC / Medicis is a sub-pixel two-dimensional stereo matching algorithm that works on an image pair. This tool is a block matching algorithm, which means that it is based on a local method. Moreover it does not regularize the results found. It proposes several matching cos… Show more

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Cited by 3 publications
(2 citation statements)
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“…The tool is planned to be integrated into The overall workflow for the absolute, band-to-band registration, and multi-temporal GQA of SEVIRI that is implemented in the final GQA Tool is given in [25]. The algorithm validation with respect to the MEDICIS Tool of CNES [52] and the traditional EUM online and offline tools of EUMETSAT are also provided in the same publication [25], along with the long-term quality monitoring results. Debacker et al [21] compared The overall workflow for the absolute, band-to-band registration, and multi-temporal GQA of SEVIRI that is implemented in the final GQA Tool is given in [25].…”
Section: Msg Sevirimentioning
confidence: 99%
“…The tool is planned to be integrated into The overall workflow for the absolute, band-to-band registration, and multi-temporal GQA of SEVIRI that is implemented in the final GQA Tool is given in [25]. The algorithm validation with respect to the MEDICIS Tool of CNES [52] and the traditional EUM online and offline tools of EUMETSAT are also provided in the same publication [25], along with the long-term quality monitoring results. Debacker et al [21] compared The overall workflow for the absolute, band-to-band registration, and multi-temporal GQA of SEVIRI that is implemented in the final GQA Tool is given in [25].…”
Section: Msg Sevirimentioning
confidence: 99%
“…This tool uses local stereo-rectification to increase matching performance and is built with a modular architecture that allows to change the matching (or disparity estimation) algorithm. In this work, matching has been carried out by the in-house correlation tool Medicis (Cournet, 2016), which seems the most appropriate given the observed landscape and allows efficiently filtering bad matches over shadows, cloud or watering areas. Some modifications were made by CNES to the S2P software.…”
Section: Dsm Generationmentioning
confidence: 99%