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Auteur Yihui Li |
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A high-resolution panchromatic-multispectral satellite image fusion method assisted with building segmentation / Fang Gao in Computers & geosciences, vol 168 (November 2022)
[article]
Titre : A high-resolution panchromatic-multispectral satellite image fusion method assisted with building segmentation Type de document : Article/Communication Auteurs : Fang Gao, Auteur ; Yihui Li, Auteur ; Peng Zhang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 105219 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] bâtiment
[Termes IGN] filtre de Gauss
[Termes IGN] fusion d'images
[Termes IGN] image à haute résolution
[Termes IGN] image Jilin
[Termes IGN] image multibande
[Termes IGN] image panchromatique
[Termes IGN] image satellite
[Termes IGN] lissage de donnéesRésumé : (auteur) The main difficulty of panchromatic-multispectral image fusion is to balance the quality of spatial information and the spectral fidelity. Most of the practical fusion methods determine the optimal parameters based on the spatial and spectral characteristics of all original panchromatic and multispectral bands. However, for built-up and non-built-up areas (like cropland, forest) in one image, there may be large differences in their spatial and spectral characteristics, so their fused results are not optimal respectively with same parameters. To address above issues, this paper presents a high-resolution satellite image fusion method assisted with building segmentation. First, the proposed approach computes the average gradient and Gaussian filtering parameters of built-up and non-built-up areas separately according to the building segmentation results, on the basis of smoothing filter-based intensity modulation (SFIM). Then the intermediate data of two types of areas are computed in parallel and they are composited to obtain the final fused image, weighted by the pixel-wise “building factors” derived from the building segmentation results. Moreover, to better simulate the spatial characteristics of the multispectral image, we perform the “gradient simulation” operation to extract the gradient values in the multispectral image. Experimental results on Jilin-1 satellite images show that the proposed method provides competitive performance in spatial resolution, multispectral fidelity and quantity of information, as compared to the state-of-the-art methods in mainstream commercial software. Numéro de notice : A2022-721 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.cageo.2022.105219 Date de publication en ligne : 11/09/2022 En ligne : https://doi.org/10.1016/j.cageo.2022.105219 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101657
in Computers & geosciences > vol 168 (November 2022) . - n° 105219[article]A high-resolution satellite DEM filtering method assisted with building segmentation / Yihui Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 6 (June 2021)
[article]
Titre : A high-resolution satellite DEM filtering method assisted with building segmentation Type de document : Article/Communication Auteurs : Yihui Li, Auteur ; Fang Gao, Auteur ; Wentao Li, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 421 - 430 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] détection du bâti
[Termes IGN] filtrage numérique d'image
[Termes IGN] filtre adaptatif
[Termes IGN] image à haute résolution
[Termes IGN] Kappa de Cohen
[Termes IGN] modèle numérique de surface
[Termes IGN] orthoimage
[Termes IGN] point d'appui
[Termes IGN] segmentation d'imageRésumé : (Auteur) Digital elevation model (DEM) filtering is critical in DEM production, and large-area meter-level resolution DEM is mainly generated from high-resolution satellite images. However, the current DEM filtering methods are mostly aimed at laser scanning data and tend to excessively remove ground points when processing a satellite digital surface model (DSM). To accurately filter out buildings and preserve terrain, we propose a DEM filtering algorithm using building segmentation results of orthophoto. Based on morphological filtering, our method estimates the probability of being a built-up area or mountains for DSM, and according to this probability the filtering parameters are adaptively adjusted. For robustness, our method performs the above filtering operation on DSM through a sliding-window approach, and finally the nonground points are determined by the votes of multiple filtering. Experiments against six representative data sets have shown that our method achieved superior performance than classical algorithms and commercial software. Numéro de notice : A2021-374 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.87.6.421 Date de publication en ligne : 01/06/2021 En ligne : https://doi.org/10.14358/PERS.87.6.421 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97827
in Photogrammetric Engineering & Remote Sensing, PERS > vol 87 n° 6 (June 2021) . - pp 421 - 430[article]Exemplaires(1)
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