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Auteur Yiguang Liu |
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Hierarchical and adaptive phase correlation for precise disparity estimation of UAV images / Jie Li in IEEE Transactions on geoscience and remote sensing, vol 54 n° 12 (December 2016)
[article]
Titre : Hierarchical and adaptive phase correlation for precise disparity estimation of UAV images Type de document : Article/Communication Auteurs : Jie Li, Auteur ; Yiguang Liu, Auteur ; Shuangli Du, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 7092 - 7104 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] appariement d'images
[Termes IGN] drone
[Termes IGN] image aérienne
[Termes IGN] modèle numérique de surface
[Termes IGN] stéréoscopieRésumé : (Auteur) When using fixed-window phase correlation (PC) to estimate the disparity of stereo images, the precision is usually rather poor due to large depth differences of scenes and noise, and this problem is specially severe when using unmanned aerial vehicle (UAV) image pairs to extract the digital elevation model of mountain land. To tackle this problem, this paper proposes a hierarchical and adaptive PC, which includes three steps: First, PC with the initialized window is performed to coarsely estimate a disparity value, along with the peak of the Dirichlet function for each pixel; then, an additional round of PC is performed for each pixel using the window of smaller size and with being guided by the coarsely estimated disparity; finally, the previous two steps are iteratively performed until convergence. In particular, using the peak of the Dirichlet function of each pixel in step two, we can drop out the influence of dramatically changing areas such as river; moreover, the scheme can minimize the influence of boundary overreach. The novel scheme has been tested on a large number of UAV images captured at mountainous regions in southwest China, showing that the proposed method is superior to the state-of-the-art methods, especially in handling UAV images of the high mountains and rivers. Numéro de notice : A2016-925 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2595861 En ligne : https://doi.org/10.1109/TGRS.2016.2595861 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83331
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 12 (December 2016) . - pp 7092 - 7104[article]