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Generic method for RPC refinement using ground control information / Z. Xiong in Photogrammetric Engineering & Remote Sensing, PERS, vol 75 n° 9 (September 2009)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 75 n° 9 (September 2009) . - pp 1083 - 1092 Titre : Generic method for RPC refinement using ground control information Type de document : Article/Communication Auteurs : Z. Xiong, Auteur ; Y. Zhang, Auteur Année de publication : 2009 Article en page(s) : pp 1083 - 1092 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes IGN] modèle par fonctions rationnelles [Termes IGN] modélisation géométrique de prise de vue [Termes IGN] orientation du capteur [Termes IGN] point d'appui Résumé : (Auteur) Geometric sensor models are used in image processing to model the relationship between object space and image space and to transform image data to conform to a map projection. An Rational Polynomial Coefficient (RCP) is a generic sensor model that can be used to transform images from a variety of different high resolution satellite and airborne remote sensing systems. To date, numerous researchers have published papers about RPC refinement, aimed at improving the accuracy of the results. So far, the Bias Compensation method is the one that is the most accepted and widely used, but this method has rigorous conditions that limit its use; namely, it can only be used to improve the RPC of images obtained from cameras with a narrow field of view and small attitude errors, such as those used on Ikonos or QuickBird satellites. In many cases, these rigorous conditions may not be satisfied (e.g., cameras with a wide field of view and some satellites with large ephemeris and attitude errors). Therefore, a more robust method that can be used to refine the RPC under a wider range of conditions is desirable. In this paper, a generic method for RPC refinement is proposed. The method first restores the sensor’s pseudo position and attitude, then adjusts these parameters using ground control points. Finally a new RPC is generated based on the sensor’s adjusted position and attitude. We commence our paper with a review of the previous ten years of research directed toward RPC refinement, and compare the characteristics of different refinement methods that have been proposed to date. We then present a methodology for a proposed generic method for RPC refinement and describe the results of two sets of experiments that compare the proposed Generic method with the Bias Compensation method. The results confirm that the Bias Compensation method works well only when the aforementioned rigorous conditions are met. The accuracy of the RPC refined by the Bias Compensation method decreased rapidly with the sensor’s position error and attitude error. In contrast to this, the Generic method proposed in this paper was found to yield highly accurate results under a variety of different sensor positions and attitudes. Copyright ASPRS Numéro de notice : A2009-370 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.75.9.1083 En ligne : https://doi.org/10.14358/PERS.75.9.1083 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30000 [article]

Error budget of Lidar systems and quality control of the derived data / A. Habib in Photogrammetric Engineering & Remote Sensing, PERS, vol 75 n° 9 (September 2009)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 75 n° 9 (September 2009) . - pp 1093 - 1108 Titre : Error budget of Lidar systems and quality control of the derived data Type de document : Article/Communication Auteurs : A. Habib, Auteur ; K.I. Bang, Auteur ; A. Kersting, Auteur ; D.C. Lee, Auteur Année de publication : 2009 Article en page(s) : pp 1093 - 1108 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] contrôle qualité [Termes IGN] données lidar [Termes IGN] erreur aléatoire [Termes IGN] erreur systématique [Termes IGN] lasergrammétrie [Termes IGN] modèle mathématique [Termes IGN] point d'appui Résumé : (Auteur) Lidar systems have been widely adopted for the acquisition of dense and accurate topographic data over extended areas. Although the utilization of this technology has increased in different applications, the development of standard methodologies for the quality assurance of lidar systems and quality control of the derived data has not followed the same trend. In other words, a lack of reliable, practical, cost-effective, and commonly-acceptable methods for quality evaluation is evident. A frequently adopted procedure for quality evaluation is the comparison between lidar data and ground control points. Besides being expensive, this approach is not accurate enough for the verification of the horizontal accuracy, which is known to be worse than the vertical accuracy. This paper is dedicated to providing an accurate, economical, and convenient quality control methodology for the evaluation of lidar data. The paper starts with a brief discussion of the lidar mathematical model, which is followed by an analysis of possible random and systematic errors and their impact on the resulting surface. Based on the discussion of error sources and their impact, a tool for evaluating the quality of the derived surface is proposed. In addition to the verification of the data quality, the proposed method can be used for evaluating the system parameters and measurements. Experimental results from simulated and real data demonstrate the feasibility of the proposed tool. Copyright ASPRS Numéro de notice : A2009-371 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.75.9.1093 En ligne : https://doi.org/10.14358/PERS.75.9.1093 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30001 [article]