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Evaluation of pan-sharpening methods for spatial and spectral quality / Jagalingam Pushparaj in Applied geomatics, vol 9 n° 1 (March 2017)
[article]
Titre : Evaluation of pan-sharpening methods for spatial and spectral quality Type de document : Article/Communication Auteurs : Jagalingam Pushparaj, Auteur ; Arkal Vittal Hegde, Auteur Année de publication : 2017 Article en page(s) : pp 1 - 12 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] algorithme de Gram-Schmidt
[Termes IGN] analyse en composantes principales
[Termes IGN] classification Spectral angle mapper
[Termes IGN] évaluation
[Termes IGN] filtre passe-haut
[Termes IGN] image multibande
[Termes IGN] image panchromatique
[Termes IGN] image Quickbird
[Termes IGN] ondelette
[Termes IGN] pansharpening (fusion d'images)
[Termes IGN] qualité géométrique (image)
[Termes IGN] qualité radiométrique (image)
[Termes IGN] transformation de Brovey
[Termes IGN] transformation intensité-teinte-saturationRésumé : (auteur) Many pan-sharpening methods have been proposed to fuse the high spectral and low spatial resolution of multispectral (MS) image with the high spatial resolution of panchromatic (PAN) image to produce a multispectral image with improved spatial resolution. In this study, the effectiveness of pan-sharpening methods such as principal component analysis (PCA), brovey transform (BT), modified intensity hue saturation (M-IHS), multiplicative, wavelet-intensity-hue-saturation (W-IHS), wavelet principal component analysis (W-PCA), hyperspectral colour space (HCS), high-pass filter (HPF), gram-schmidt (GS), subtractive resolution merge (SRM), Fuze Go and Ehlers was assessed and compared by fusing the PAN and MS imagery of Quickbird-2. The qualities of the pan-sharpening methods were evaluated by both visual and quantitative analyses with respect to spatial and spectral fidelity. In quantitative analysis, the spectral indices such as spectral angle mapper (SAM), relative dimensionless global error in synthesis (ERGAS), structural similarity index method (SSIM), relative average spectral error (RASE), correlation coefficient (CC) and universal image quality index (Q) were used. The spatial indices such as spatial correlation coefficient (SCC), gradient and image entropy (E) were used. The result of both analyses revealed that the Ehlers and Fuze Go methods performed better than the other methods. The Ehlers method was superior by retaining the colour information, and Fuze Go best enhanced the spatial details in the fused image. Numéro de notice : A2017-357 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s12518-016-0179-2 Date de publication en ligne : 13/12/2016 En ligne : http://doi.org/10.1007/s12518-016-0179-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85763
in Applied geomatics > vol 9 n° 1 (March 2017) . - pp 1 - 12[article]