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A GIHS-based spectral preservation fusion method for remote sensing images using edge restored spectral modulation / Xiran Zhou in ISPRS Journal of photogrammetry and remote sensing, vol 88 (February 2014)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 88 (February 2014) . - pp 16 - 27 Titre : A GIHS-based spectral preservation fusion method for remote sensing images using edge restored spectral modulation Type de document : Article/Communication Auteurs : Xiran Zhou, Auteur ; Jun Liu, Auteur ; Lei Cao, Auteur ; Qiming Zhou, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 16 - 27 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] algorithme de fusion [Termes IGN] appariement d'histogramme [Termes IGN] filtrage numérique d'image [Termes IGN] fusion d'images [Termes IGN] image multibande [Termes IGN] modulation de fréquence [Termes IGN] qualité d'image [Termes IGN] transformation intensité-teinte-saturation Résumé : (Auteur) High spatial resolution and spectral fidelity are basic standards for evaluating an image fusion algorithm. Numerous fusion methods for remote sensing images have been developed. Some of these methods are based on the intensity–hue–saturation (IHS) transform and the generalized IHS (GIHS), which may cause serious spectral distortion. Spectral distortion in the GIHS is proven to result from changes in saturation during fusion. Therefore, reducing such changes can achieve high spectral fidelity. A GIHS-based spectral preservation fusion method that can theoretically reduce spectral distortion is proposed in this study. The proposed algorithm consists of two steps. The first step is spectral modulation (SM), which uses the Gaussian function to extract spatial details and conduct SM of multispectral (MS) images. This method yields a desirable visual effect without requiring histogram matching between the panchromatic image and the intensity of the MS image. The second step uses the Gaussian convolution function to restore lost edge details during SM. The proposed method is proven effective and shown to provide better results compared with other GIHS-based methods. Numéro de notice : A2014-081 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.11.011 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.11.011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32986 [article]

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