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Optimizing the high-pass filter addition technique for image fusion / U.G. Gangkofner in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 9 (September 2008)
[article]
Titre : Optimizing the high-pass filter addition technique for image fusion Type de document : Article/Communication Auteurs : U.G. Gangkofner, Auteur ; P.S. Pradhan, Auteur ; D.W. Holcomb, Auteur Année de publication : 2008 Article en page(s) : pp 1107 - 1118 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] filtrage numérique d'image
[Termes IGN] filtre passe-haut
[Termes IGN] fusion d'images
[Termes IGN] image à basse résolution
[Termes IGN] image à très haute résolution
[Termes IGN] image optique
[Termes IGN] netteté
[Termes IGN] transformation en ondelettesRésumé : (Auteur) Pixel-level image fusion combines complementary image data, most commonly low spectral-high spatial resolution data with high spectral-low spatial resolution optical data. The presented study aims at refining and improving the High-Pass Filter Additive (HPFA) fusion method towards a tunable and versatile, yet standardized image fusion tool. HPFA is an image fusion method in the spatial domain, which inserts structural and textural details of the higher resolution image into the lower resolution image, whose spectral properties are thereby largely retained. Using various input image pairs, workable sets of HPFA parameters have been derived with regard to high-pass filter properties and injection weights. Improvements are the standardization of the HPFA parameters over a wide range of image resolution ratios and the controlled trade-off between resulting image sharpness and spectral properties. The results are evaluated visually and by spectral and spatial metrics in comparison with wavelet-based image fusion results as a benchmark. Copyright ASPRS Numéro de notice : A2008-347 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.74.9.1107 En ligne : https://doi.org/10.14358/PERS.74.9.1107 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29340
in Photogrammetric Engineering & Remote Sensing, PERS > vol 74 n° 9 (September 2008) . - pp 1107 - 1118[article]Comparison of nine fusion techniques for very high resolution data / K.G. Nikolapoulos in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 5 (May 2008)
[article]
Titre : Comparison of nine fusion techniques for very high resolution data Type de document : Article/Communication Auteurs : K.G. Nikolapoulos, Auteur Année de publication : 2008 Article en page(s) : pp 647 - 659 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] analyse en composantes principales
[Termes IGN] distorsion d'image
[Termes IGN] fusion d'images
[Termes IGN] image à résolution submétrique
[Termes IGN] image à très haute résolution
[Termes IGN] image multibande
[Termes IGN] image panchromatique
[Termes IGN] image Quickbird
[Termes IGN] pansharpening (fusion d'images)
[Termes IGN] qualité des données
[Termes IGN] transformation de Brovey
[Termes IGN] transformation en ondelettes
[Termes IGN] transformation intensité-teinte-saturationRésumé : (Auteur) The term “image fusion” covers multiple techniques used to combine the geometric detail of a high-resolution panchromatic image and the color information of a low-resolution multispectral image to produce a final image with the highest possible spatial information content while still preserving good spectral information quality. During the last twenty years, many methods such as Principal Component Analysis (PCA), Multiplicative Transform, Brovey Transform, and IHS Transform have been developed producing good quality fused images. Despite the quite good visual results, many research papers have reported the limitations of the above fusion techniques. The most significant problem is color distortion. Another common problem is that the fusion quality often depends upon the operator’s fusion experience and upon the data set being fused. In this study, we compare the efficiency of nine fusion techniques and more specifically the efficiency of IHS, Modified IHS, PCA, Pansharp, Wavelet, LMM (Local Mean Matching), LMVM (Local Mean and Variance Matching), Brovey, and Multiplicative fusion techniques for the fusion of QuickBird data. The suitability of these fusion techniques for various applications depends on the spectral and spatial quality of the fused images. In order to quantitatively measure the quality of the fused images, we have made the following controls. First, we have examined the visual qualitative result. Then, we examined the correlation between the original multispectral and the fused images and all the statistical parameters of the histograms of the various frequency bands. Finally, we performed an unsupervised classification, and we compared the resulting images. All the fusion techniques improve the resolution and the visual result. The resampling method practically has no effect on the final visual result. The LMVM, the LMM, the Pansharp, and the Wavelet merging technique do not change the statistical parameters of the original images. The Modified IHS provokes minor changes to the statistical parameters than the classical IHS or than the PCA. After all the controls, the LMVM, the LMM, the Pansharp, and the Modified IHS algorithm seem to gather the more advantages in fusion panchromatic and multispectral data. Copyright ASPRS Numéro de notice : A2008-178 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.74.5.647 En ligne : https://doi.org/10.14358/PERS.74.5.647 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29173
in Photogrammetric Engineering & Remote Sensing, PERS > vol 74 n° 5 (May 2008) . - pp 647 - 659[article]Effects of spatial resolution ratio in image fusion / Y. Ling in International Journal of Remote Sensing IJRS, vol 29 n° 7 (April 2008)
[article]
Titre : Effects of spatial resolution ratio in image fusion Type de document : Article/Communication Auteurs : Y. Ling, Auteur ; Manfred Ehlers, Auteur ; E. Usery, Auteur ; Marguerite Madden, Auteur Année de publication : 2008 Article en page(s) : pp 2157 - 2167 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] fusion d'images
[Termes IGN] image à basse résolution
[Termes IGN] image à haute résolution
[Termes IGN] image multibande
[Termes IGN] image panchromatique
[Termes IGN] limite de résolution géométriqueRésumé : (Auteur) In image fusion, the spatial resolution ratio can be defined as the ratio between the spatial resolution of the high-resolution panchromatic image and that of the low-resolution multispectral image. This paper attempts to assess the effects of the spatial resolution ratio of the input images on the quality of the fused image. Experimental results indicate that a spatial resolution ratio of 1 : 10 or higher is desired for optimal multisensor image fusion provided the input panchromatic image is not downsampled to a coarser resolution. Due to the synthetic pixels generated from resampling, the quality of the fused image decreases as the spatial resolution ratio decreases (e.g. from 1 : 10 to 1 : 30). However, even with a spatial resolution ratio as small as 1 : 30, the quality of the fused image is still better than the original multispectral image alone for feature interpretation. In cases where the spatial resolution ratio is too small (e.g. 1 : 30), to obtain better spectral integrity of the fused image, one may downsample the input high-resolution panchromatic image to a slightly lower resolution before fusing it with the multispectral image. Copyright Taylor & Francis Numéro de notice : A2008-098 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160701408345 En ligne : https://doi.org/10.1080/01431160701408345 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29093
in International Journal of Remote Sensing IJRS > vol 29 n° 7 (April 2008) . - pp 2157 - 2167[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 080-08051 RAB Revue Centre de documentation En réserve L003 Disponible ISRV: an improved synthetic variable ratio method for image fusion / L. Wang in Geocarto international, vol 23 n° 2 (April - May 2008)
[article]
Titre : ISRV: an improved synthetic variable ratio method for image fusion Type de document : Article/Communication Auteurs : L. Wang, Auteur ; X. Cao, Auteur ; J. Chen, Auteur Année de publication : 2008 Article en page(s) : pp 155 - 165 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] affinage d'image
[Termes IGN] classification dirigée
[Termes IGN] ENVI
[Termes IGN] fusion d'images
[Termes IGN] image à résolution métrique
[Termes IGN] image Ikonos
[Termes IGN] image multibande
[Termes IGN] image panchromatiqueRésumé : (Auteur) An Improved Synthetic Variable Ratio (ISVR) fusion method is proposed to merge high spatial resolution panchromatic (Pan) images and multispectral (MS) images based on a simulation of the panchromatic image from the multispectral bands. Compared to the existing SVR (Synthetic Variable Ratio) family methods, the ISVR method manifests two major improvements: a simplified and physically meaningful scheme to derive the parameters necessary as required by SVR, and less computing power. Two sets of IKONOS Pan and MS images: one in urban area and another one in a forest area, were used to evaluate the effectiveness of classification-oriented ISVR method in comparison to the Principal Component Substitution (PCS), Synthetic Variable Ratio (SVR) and Gram-Schmidt Spectral Sharpening (GS) methods that are available in the ENVI software package. Results indicate the ISVR method achieves the best spectral fidelity to facilitate classification compared to PCS, SVR, and GS methods. Copyright Taylor & Francis Numéro de notice : A2008-079 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106040701204198 En ligne : https://doi.org/10.1080/10106040701204198 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29074
in Geocarto international > vol 23 n° 2 (April - May 2008) . - pp 155 - 165[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-08021 RAB Revue Centre de documentation En réserve L003 Disponible Land-cover classification using ASTER: multi-band combinations based on wavelet fusion and SOM neural network / H. Bagan in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 3 (March 2008)
[article]
Titre : Land-cover classification using ASTER: multi-band combinations based on wavelet fusion and SOM neural network Type de document : Article/Communication Auteurs : H. Bagan, Auteur ; Q. Wang, Auteur ; et al., Auteur Année de publication : 2008 Article en page(s) : pp 333 - 342 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] carte de Kohonen
[Termes IGN] classification par réseau neuronal
[Termes IGN] fusion d'images
[Termes IGN] image multibande
[Termes IGN] image Terra-ASTER
[Termes IGN] occupation du sol
[Termes IGN] précision de la classificationRésumé : (Auteur) In this study, we developed a land-cover classification methodology using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) visible near-infrared (VNIR), shortwave infrared (SWIR), and thermal infrared (TIR) band combinations based on wavelet fusion and the selforganizing map (SOM) neural network methods, and compared the classification accuracies of different combinations of ASTER multi-band data. A wavelet fusion concept named ARSIS (Amélioration de la Résolution Spatiale par Injection de Structures) was used to fuse ASTER data in the preprocessing stage. In order to apply the wavelet fusion method to ASTER data, the principal components of ASTER VNIR data were computed. The first principal component was used as the base image for wavelet fusion. In our experiments, the spatial resolution of ASTER VNIR, SWIR, and TIR data was adjusted to the same 15 m. SOM classification accuracy was increased from 83 percent to 93 percent by this fusion, and classification accuracy increased along with the increase of band numbers. Classification accuracy reaches the highest value when all 14 bands are used, but classification accuracy closely approached the highest value when three VNIR bands, three SWIR bands, and two TIR bands were used. A similar tendency was also obtained by the maximum likelihood classification (MLC) method, but the classification accuracies of MLC over all band combinations were considerably obviously lower than those obtained by the SOM method. Copyright ASPRS Numéro de notice : A2008-075 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.74.3.333 En ligne : https://doi.org/10.14358/PERS.74.3.333 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29070
in Photogrammetric Engineering & Remote Sensing, PERS > vol 74 n° 3 (March 2008) . - pp 333 - 342[article]Comparison and improvement of wavelet-based image fusion / G. Hong in International Journal of Remote Sensing IJRS, vol 29 n°3-4 (February 2008)PermalinkLand-cover change and environmental impact analysis in the Greater Mankato area of Minnesota using remote sensing and GIS modelling / F. Yuan in International Journal of Remote Sensing IJRS, vol 29 n°3-4 (February 2008)PermalinkGlobal elevation ancillary data for land-use classification using granular neural networks / D. Stathakis in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 1 (January 2008)PermalinkImagerie spatiale / P. Lier (2008)PermalinkFusion of support vector machines for classification of multisensor data / Björn Waske in IEEE Transactions on geoscience and remote sensing, vol 45 n° 12 Tome 1 (December 2007)PermalinkLand-cover classification in the Brazilian Amazon with the integration of Landsat ETM+ and Radarsat data / Dong Lu in International Journal of Remote Sensing IJRS, vol 28 n°23-24 (December 2007)PermalinkFusing Ikonos images by a four-band wavelet transformation method / Wei Shi in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 11 (November 2007)PermalinkRegenerating boreal forest structure estimation using SPOT-5 pan-sharpened imagery / A.L. Wunderle in International Journal of Remote Sensing IJRS, vol 28 n°19-20 (October 2007)PermalinkIntegration of Ikonos and Quickbird imagery for geopositioning accuracy analysis / R. Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 9 (September 2007)PermalinkMultispectral images fusion by a joint multidirectional and multiresolution representation / M. Lillo-Saaverda in International Journal of Remote Sensing IJRS, vol 28 n°17-18 (September 2007)Permalink