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Dépouillements

A comparison of four common atmospheric correction methods / A.S. Mahiny in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 4 (April 2007)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 73 n° 4 (April 2007) . - pp 361 - 368 Titre : A comparison of four common atmospheric correction methods Type de document : Article/Communication Auteurs : A.S. Mahiny, Auteur ; B. Turner, Auteur Année de publication : 2007 Article en page(s) : pp 361 - 368 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse comparative [Termes IGN] correction atmosphérique [Termes IGN] détection de changement [Termes IGN] erreur absolue [Termes IGN] erreur relative [Termes IGN] image Landsat-TM Résumé : (Auteur) Four atmospheric correction methods, two relative and two absolute, were compared in this study. Two of the methods (PIF and RCS) were relative approaches; COST is an absolute image-based method and 6S, an absolute modeling method. The methods were applied to the hazy bands 1 through 4 of a Landsat TM scene of the year 1997, which was being used in a change detection project. The effects of corrections were studied in woodland patches. Three criteria, namely (a) image attributes; (b) image classification results, and (c) landscape metrics, were used for comparing the performance of the correction methods. Average pixel values, dynamic range, and coefficient of variation of bands constituted the first criterion, the area of detected vegetation through image classification was the second criterion, and patch and landscape measures of vegetation the third criterion. Overall, the COST, RCS, and 6S methods performed better than PIF and showed more stable results. The 6S method produced some negative values in bands 2 through 4 due to the unavailability of some data needed in the model. Having to use only a single set of image pixels for normalization in the PIF method and the difficulty of selecting such samples in the study area may be the reasons for its poor performance. Copyright ASPRS Numéro de notice : A2007-140 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.73.4.361 En ligne : https://doi.org/10.14358/PERS.73.4.361 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28503 [article]

A rigorous laboratory calibration method for interior orientation of an airborne linear push-broom camera / Tianen Chen in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 4 (April 2007)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 73 n° 4 (April 2007) . - pp 369 - 374 Titre : A rigorous laboratory calibration method for interior orientation of an airborne linear push-broom camera Type de document : Article/Communication Auteurs : Tianen Chen, Auteur ; Ryosuke Shibasaki, Auteur ; Z. Lin, Auteur Année de publication : 2007 Article en page(s) : pp 369 - 374 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes IGN] ADS40 [Termes IGN] capteur aérien [Termes IGN] capteur en peigne [Termes IGN] étalonnage de chambre métrique [Termes IGN] étalonnage radiométrique [Termes IGN] étalonnage spectral [Termes IGN] image à haute résolution [Termes IGN] limite de résolution géométrique [Termes IGN] orientation interne Résumé : (Auteur) The linear push-broom camera is one of the most important imaging systems in modern photogrammetry and remote sensing to collect high-resolution digital panchromatic and multispectral images for comprehensive evaluation of natural resources and environmental conditions. Most commercial high-resolution satellites such as SPOT-5, Ikonos-2, and QuickBird use similar sensors. Airborne sensors such as the ADS40 and STARIMAGER® also use the push-broom approach to collect multi-channel, seamless image strips for linear objects such as roads, railways, rivers, seashores, electric power lines, pipe lines, and high-rise building areas. Other commercial hyperspectral sensors also use the push-broom approach to collect digital images for remote sensing applications. High performance linear cameras require high resolution geometric, spectral, and radiometric calibration. This topic has not been covered in the scientific literature. Although the self-calibration is successful to compute the calibration parameters of frame camera, it is denied in our tests since the linear camera’s calibrated parameters are dependent on the accuracy of on-board GPS/IMU position and attitude data. In this paper, a rigorous calibration method is presented. This approach has been successfully used in our developed airborne three-line scanner (TLS) imaging system STARIMAGER® in the last five years. The method can accurately compute TLS’s focal length, principle point location, lens distortion, CCD pixel size, CCD curve deformation, and convergence angles between each CCD line sensor on the focal plane. Without any modification, it can be directly applied to single linear sensors and multi-linear sensors. Copyright ASPRS Numéro de notice : A2007-141 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.73.4.369 En ligne : https://doi.org/10.14358/PERS.73.4.369 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28504 [article]

Generation of orthoimages and perspective views with automatic visibility checking and texture blending / G.E. Karras in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 4 (April 2007)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 73 n° 4 (April 2007) . - pp 403 - 411 Titre : Generation of orthoimages and perspective views with automatic visibility checking and texture blending Type de document : Article/Communication Auteurs : G.E. Karras, Auteur ; L. Grammatikopoulos, Auteur ; I. Kalisperakis, Auteur ; E. Petsa, Auteur Année de publication : 2007 Article en page(s) : pp 403 - 411 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] algorithme de fusion [Termes IGN] données laser [Termes IGN] fusion de données [Termes IGN] orthoimage [Termes IGN] précision géométrique (imagerie) [Termes IGN] restitution 3D [Termes IGN] texture d'image Résumé : (Auteur) Conventional orthorectification software cannot handle surface occlusions and image visibility. The approach presented here synthesizes related work in photogrammetry and computer graphics/vision to automatically produce orthographic and perspective views based on fully 3D surface data (supplied by laser scanning). Surface occlusions in the direction of projection are detected to create the depth map of the new image. This information allows identifying, by visibility checking through back-projection of surface triangles, all source images which are entitled to contribute color to each pixel of the novel image. Weighted texture blending allows regulating the local radiometric contribution of each source image involved, while outlying color values are automatically discarded with a basic statistical test. Experimental results from a close-range project indicate that this fusion of laser scanning with multi-view photogrammetry could indeed combine geometric accuracy with high visual quality and speed. A discussion of intended improvements of the algorithm is also included. Copyright ASPRS Numéro de notice : A2007-142 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.73.4.403 En ligne : https://doi.org/10.14358/PERS.73.4.403 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28505 [article]

Improving land-cover classification using recognition threshold neural networks / M.J. Aitkenhead in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 4 (April 2007)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 73 n° 4 (April 2007) . - pp 413 - 421 Titre : Improving land-cover classification using recognition threshold neural networks Type de document : Article/Communication Auteurs : M.J. Aitkenhead, Auteur ; R. Dyer, Auteur Année de publication : 2007 Article en page(s) : pp 413 - 421 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] carte d'occupation du sol [Termes IGN] classification dirigée [Termes IGN] classification par réseau neuronal [Termes IGN] image Landsat [Termes IGN] Philippines [Termes IGN] seuillage d'image [Termes IGN] surface cultivée Résumé : (Auteur) The use of neural networks to classify land-cover from remote sensing imagery relies on the ability to determine a winner from the candidate land-cover types based on the imagery information available. In the case of a “winner- takes-all” scenario, this does not allow us a measure of how much the prediction of each pixel’s land-cover can be trusted. We present a three-stage method where only winning candidates which are given a clear lead over the other land-cover types are accepted, with a neighborhood relationship and the application of mixed pixels being used to provide full classification. This method allows us to place more faith in the resulting map than simply taking the winner, and results in a higher accuracy of classification. The method is applied to Landsat imagery of an area of the Philippines where natural, urban, and cultivated land-cover types exist. Copyright ASPRS Numéro de notice : A2007-143 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.73.4.413 En ligne : https://doi.org/10.14358/PERS.73.4.413 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28506 [article]