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Camera self-calibration with lens distortion from a single image / Dan Liu 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 325 - 334 Titre : Camera self-calibration with lens distortion from a single image Type de document : Article/Communication Auteurs : Dan Liu, Auteur ; Xuejun Liu, Auteur ; Meizhen Wang, Auteur Année de publication : 2016 Article en page(s) : pp 325 - 334 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes IGN] auto-étalonnage [Termes IGN] contrainte géométrique [Termes IGN] étalonnage de capteur (imagerie) [Termes IGN] photogrammétrie terrestre Résumé : (Auteur) This paper presents an effective approach for self-calibration with lens distortion using a single image combined with geometric constraints including vanishing points and ellipses. To improve the accuracy of self-calibration, radial distortion and distortion center are included in the calibration procedure. First, assuming image center as the symmetric center, the first radial distortion coefficient and vanishing points are simultaneously optimized from line segments in the image. Second, by utilizing the optimized vanishing points and extracted ellipse, principal distance and principal point are estimated. Last, distortion center is set as the current calculated principal point, and the above steps are then repeated until the principal point reaches a stable solution. Extensive quantitative and qualitative studies of the approach are performed. The experiments pertaining to simulated and real images demonstrate that the approach is effective and suitable and that the approach obtains satisfactory results. Numéro de notice : A2016-409 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.82.5.325 En ligne : http://dx.doi.org/10.14358/PERS.82.5.325 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81274 [article]

ICESat/GLAS canopy height sensitivity inferred from Airborne Lidar / Craig Mahoney 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 351 - 363 Titre : ICESat/GLAS canopy height sensitivity inferred from Airborne Lidar Type de document : Article/Communication Auteurs : Craig Mahoney, Auteur ; Christopher Hopkinson, Auteur ; Alex Held, Auteur ; Natascha Kljun, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 351 - 363 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] altimétrie satellitaire par laser [Termes IGN] analyse comparative [Termes IGN] biomasse forestière [Termes IGN] données ICEsat [Termes IGN] données lidar [Termes IGN] hauteur des arbres [Termes IGN] semis de points [Termes IGN] télémétrie laser aéroporté Résumé : (Auteur) Variations in laser properties and data acquisition times introduced inconsistencies in Geoscience Laser Altimeter System (GLAS) data. The effect of data inconsistencies, on two GLAS height retrieval methods, from three study sites, are investigated and validated against airborne laser scanning (ALS) percentile heights, from three data sources: all/first return point clouds, and raster canopy height models. GLAS/ALS controls were established as a basis against which the influence of laser number, transmission energy, and seasonality were assessed through comparison statistics. The favored GLAS height method best compared with ALS 95th percentile heights from an all return point cloud. Optimal GLAS data (R2 = 0.69, RMSE = 8.10 m) were noted when GLAS acquired data during summertime from high energy, laser three transmissions. As GLAS data can be used in global biomass assessments, there is a need to understand and quantify the influence of these data inconsistencies on canopy height estimates. Numéro de notice : A2016-410 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.82.5.351 En ligne : http://dx.doi.org/10.14358/PERS.82.5.351 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81276 [article]

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]

Autonomous ortho-rectification of very high resolution imagery using SIFT and genetic algorithm / Pramod Kumar Konugurthi 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 377 - 388 Titre : Autonomous ortho-rectification of very high resolution imagery using SIFT and genetic algorithm Type de document : Article/Communication Auteurs : Pramod Kumar Konugurthi, Auteur ; Raghavendra Kune, Auteur ; Ravi Nooka, Auteur ; Venkatraman Sarma, Auteur Année de publication : 2016 Article en page(s) : pp 377 - 388 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] algorithme génétique [Termes IGN] appariement d'images [Termes IGN] chaîne de traitement [Termes IGN] image à très haute résolution [Termes IGN] orthorectification [Termes IGN] point d'appui [Termes IGN] SIFT (algorithme) Résumé : (Auteur) Ortho-rectification of very high resolution imagery from agile platforms using Rigorous Sensor Model / Rational Functional Model is quite challenging and demands a fair amount of interactivity in Ground Control Point (GCP) identification/selection for refining the model and for final product evaluation. The paper proposes achieving complete automation in the ortho-rectification process by eliminating all the interactive components, and incorporating fault tolerance mechanisms within the model to make the process robust and reliable. The key aspects proposed in this paper are: two stage Scale Invariant Feature Transform (SIFT) based matching to obtain a large numbers of checkpoints using much coarser resolution images such as Landsat/ETM+, followed by a GA to select the right combination of minimal GCPS based on minimizing Root Mean Square Error (RMSE) and maximizing the area covered under GCPS, and finally, a decision rule based product evaluation to make the process operate in an "autonomous closed loop mode". The method is generic and has been tested on hundreds of Cartosat-1/2 images, and has achieved above 90% reliability with sub-pixel relative error of reference data. Numéro de notice : A2016-412 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.82.5.377 En ligne : http://dx.doi.org/10.14358/PERS.82.5.377 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81279 [article]