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Support vector machines regression for retrieval of leaf area index from multiangle imaging spectroradiometer / S. Durbha in Remote sensing of environment, vol 107 n° 1-2 (15 March 2007)  

Public [article]  inRemote sensing of environment > vol 107 n° 1-2 (15 March 2007) . - pp 348 - 361 Titre : Support vector machines regression for retrieval of leaf area index from multiangle imaging spectroradiometer Type de document : Article/Communication Auteurs : S. Durbha, Auteur ; R.l. King, Auteur ; N.H. Younan, Auteur Année de publication : 2007 Article en page(s) : pp 348 - 361 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] image Terra-MISR [Termes IGN] Leaf Area Index [Termes IGN] modèle de transfert radiatif [Termes IGN] problème inverse [Termes IGN] régression Résumé : (Auteur) The retrieval of biophysical variables using canopy reflectance models is hindered by the fact that the inverse problem is ill posed. This is due to the measurement, model errors and the inadequacy between the model and reality, which produces similar reflectances for the different combination of the input parameters into the radiative transfer model. This leads to unstable and often inaccurate inversion results. The ill-posed nature of the inverse problem requires some regularization. Regularization means that one tries to consider only those solutions that are in the proximity of the true value. In order to regularize the model inversion, we propose kernel-based regularization by support vector machines regression (SVR) method. The formulation of the SVR contains meta-parameters C (regularization) and ?-insensitive loss. The SVR generalization performance (estimation accuracy) depends on these two parameters and the kernel parameters. Often the meta-parameters are selected using prior knowledge and/or user expertise. In this paper we adopt methods for the estimation of the meta-parameters from the input data itself instead of relying on any prior information. This paper is focused on the retrieval of leaf area index (LAI) from multiangle imaging spectroradiometer (MISR) data. The proposed methodology was implemented by inverting a 1D canopy reflectance model (PROSAIL) using SVR over MISR data. The results were validated against the LAI retrievals at the Alpilles EOS validation core site. An RMSE of 0.64 was obtained using both near-infrared (NIR) in conjunction with the red band and an RMSE of 0.50 using only the NIR band. Copyright Elsevier Numéro de notice : A2007-057 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2006.09.031 En ligne : https://doi.org/10.1016/j.rse.2006.09.031 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28422 [article]

Estimation of the number of decomposition levels for a wavelet-based multiresolution multisensor image fusion / P. Pradhan in IEEE Transactions on geoscience and remote sensing, vol 44 n° 12 (December 2006)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 44 n° 12 (December 2006) . - pp 3674 - 3686 Titre : Estimation of the number of decomposition levels for a wavelet-based multiresolution multisensor image fusion Type de document : Article/Communication Auteurs : P. Pradhan, Auteur ; R.l. King, Auteur ; et al., Auteur Année de publication : 2006 Article en page(s) : pp 3674 - 3686 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] fusion d'images [Termes IGN] image multibande [Termes IGN] image panchromatique [Termes IGN] limite de résolution géométrique [Termes IGN] qualité géométrique (image) [Termes IGN] qualité radiométrique (image) [Termes IGN] transformation en ondelettes Résumé : (Auteur) The wavelet-based scheme for the fusion of multispectral (MS) and panchromatic (PAN) imagery has become quite popular due to its ability to preserve the spectral fidelity of the MS imagery while improving its spatial quality. This is important if the resultant imagery is used for automatic classification. Wavelet-based fusion results depend on the number of decomposition levels applied in the wavelet transform. Too few decomposition levels result in poor spatial quality fused images. On the other hand, too many levels reduce the spectral similarity between the original MS and the pan-sharpened images. If the shift-invariant wavelet transform is applied, each excessive decomposition level results in a large computational penalty. Thus, the choice of the number of decomposition levels is significant. In this paper, PAN and MS image pairs with different resolution ratios were fused using the shift-invariant wavelet transform, and the optimal decomposition levels were determined for each resolution ratio. In general, it can be said that the fusion of images with larger resolution ratios requires a higher number of decomposition levels. This paper provides the practitioner an understanding of the tradeoffs associated with the computational demand and the spatial and spectral quality of the wavelet-based fusion algorithm as a function of the number of decomposition levels. Copyright IEEE Numéro de notice : A2006-560 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2006.881758 En ligne : https://doi.org/10.1109/TGRS.2006.881758 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28283 [article]

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Code-barres	Cote	Support	Localisation	Section	Disponibilité
065-06121	RAB	Revue	Centre de documentation	En réserve L003	Disponible