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An improved approach based on terrain-dependent mathematical models for georeferencing pushbroom satellite images / Behrooz Moradi in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 1 (January 2021)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 87 n° 1 (January 2021) . - pp 53 - 69 Titre : An improved approach based on terrain-dependent mathematical models for georeferencing pushbroom satellite images Type de document : Article/Communication Auteurs : Behrooz Moradi, Auteur ; Mohammad Javad Valadan Zoej, Auteur ; Sayad Yaghoobi, Auteur ; Somayeh Yavari, Auteur Année de publication : 2021 Article en page(s) : pp 53 - 69 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] géoréférencement [Termes IGN] image à haute résolution [Termes IGN] image Geoeye [Termes IGN] image Ikonos [Termes IGN] Iran [Termes IGN] modèle géométrique de prise de vue [Termes IGN] modèle par fonctions rationnelles [Termes IGN] modélisation 3D Résumé : (Auteur) Recently, linear features in remotely sensed imagery have gained much attention because of their unique characteristics compared to other control features. For georeferencing high-resolution satellite images, the observations in the mathematical equations (slope and y-intercept) of the corresponding control lines in the two spaces are considered the same based on recent studies. However, the use of such assumptions causes error and reduces the accuracy of registration. The aim of this article is to present a methodology based on a quasi-observation assumption in the mathematical equations in the process of georeferencing. Experimental results for IKONOS and GeoEye images over two different cities of Iran indicate that the quasi-observation assumption can increase the average registration accuracy up to 48.96% and 24.77% using 3D-affine and rational function models, respectively. This improvement in accuracy increases the processing time by 31.48% over traditional approaches; however, the proposed methodology can be regarded as an efficient solution. Numéro de notice : A2021-057 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.87.1.53 Date de publication en ligne : 01/01/2021 En ligne : https://doi.org/10.14358/PERS.87.1.53 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96768 [article]

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A novel automatic structural linear feature-based matching method based on new concepts of mathematically-generated-points and lines / Somayeh Yavari in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 5 (May 2016)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 5 (May 2016) . - pp 365 - 376 Titre : A novel automatic structural linear feature-based matching method based on new concepts of mathematically-generated-points and lines Type de document : Article/Communication Auteurs : Somayeh Yavari, Auteur ; Mohammad Javad Valadan Zoej, Auteur ; Mahmod Reza Sahebi, Auteur ; Mehdi Mokhtarzade, Auteur Année de publication : 2016 Article en page(s) : pp 365 - 376 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] accentuation d'image [Termes IGN] appariement de données localisées [Termes IGN] appariement de formes [Termes IGN] espace objet [Termes IGN] ligne caractéristique Résumé : (Auteur) This paper investigates reliable automatic high resolution image to map matching using a novel structural linear feature-based matching (SLIM) method. The main components used by this method are the specific patterns as well as the lines and points generated mathematically. These components are produced by extension and intersection of extracted line-segments. Due to the high numbers of extracted line-segments in both image and object space, the number of possible patterns is very high. In order to decrease the search space, the innovative SLIM method is performed in three main phases. In the first phase, using a new weighting procedure, only optimum numbers of high-qualified well-distributed patterns, which are more likely to have any correspondence in object space, are selected. In the second phase, the aim is to find a pair with maximum numbers of conjugate lines. To do so, all the possible patterns in object space are screened for each selected image pattern using four predefined geometric criteria. Simultaneously, the correspondence of the other crossing lines is also determined in the same manner. In third phase, the pair with maximum numbers of matched-lines is selected among all the results of second phase. Additionally, the final-phase is done to increase the amount of correctly matched-lines. The main contribution of this investigation is automatic and correct matching of linear features with no need to any initial information. Additionally, the end-points of the corresponding lines are not necessarily conjugate points. The results show the high potential of the proposed method in terms of accuracy, reliability, automation, and time reduction even in images with repetitive patterns or a high numbers of outliers. Numéro de notice : A2016-411 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.82.5.365 En ligne : http://dx.doi.org/10.14358/PERS.82.5.365 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81277 [article]