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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]Forestry applications of UAVs in Europe: a review / Chiara Torresan in International Journal of Remote Sensing IJRS, vol 38 n° 8-10 (April 2017)
[article]
Titre : Forestry applications of UAVs in Europe: a review Type de document : Article/Communication Auteurs : Chiara Torresan, Auteur ; Andrea Berton, Auteur ; Federico Caretenuto, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 2427 - 2447 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] classification
[Termes IGN] données dendrométriques
[Termes IGN] données lidar
[Termes IGN] drone
[Termes IGN] image hyperspectrale
[Termes IGN] rayonnement lumineux
[Termes IGN] règlement
[Termes IGN] surveillance forestièreRésumé : (auteur) Unmanned aerial vehicles (UAVs) or remotely piloted aircraft systems are new platforms that have been increasingly used over the last decade in Europe to collect data for forest research, thanks to the miniaturization and cost reduction of GPS receivers, inertial navigation system, computers, and, most of all, sensors for remote sensing.
In this review, after describing the regulatory framework for the operation of UAVs in the European Union (EU), an overview of applications in forest research is presented, followed by a discussion of the results obtained from the analysis of different case studies.
Rotary-wing and fixed-wing UAVs are equally distributed among the case studies, while ready-to-fly solutions are preferred over self-designed and developed UAVs. Most adopted technologies are visible-red, green, and blue, multispectral in visible and near-infrared, middle-infrared, thermal infrared imagery, and lidar.
The majority of current UAV-based applications for forest research aim to inventory resources, map diseases, classify species, monitor fire and its effects, quantify spatial gaps, and estimate post-harvest soil displacement.
Successful implementation of UAVs in forestry depends on UAV features, such as flexibility of use in flight planning, low cost, reliability and autonomy, and capability of timely provision of high-resolution data.
Unfortunately, the fragmented regulations among EU countries, a result of the lack of common rules for operating UAVs in Europe, limit the chance to operate within Europe’s boundaries and prevent research mobility and exchange opportunities. Nevertheless, the applications of UAVs are expanding in different domains, and the use of UAVs in forestry will increase, possibly leading to a regular utilization for small-scale monitoring purposes in Europe when recent technologies (i.e. hyperspectral imagery and lidar) and methodological approaches will be consolidated.Numéro de notice : A2017-681 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431161.2016.1252477 En ligne : http://dx.doi.org/10.1080/01431161.2016.1252477 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=87243
in International Journal of Remote Sensing IJRS > vol 38 n° 8-10 (April 2017) . - pp 2427 - 2447[article]Hyperspectral band selection from statistical wavelet models / Siwei Feng in IEEE Transactions on geoscience and remote sensing, vol 55 n° 4 (April 2017)
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Titre : Hyperspectral band selection from statistical wavelet models Type de document : Article/Communication Auteurs : Siwei Feng, Auteur ; Yuki Itoh, Auteur ; Mario Parente, Auteur ; Marco F. Duarte, Auteur Année de publication : 2017 Article en page(s) : pp 2111 - 2123 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] chaîne de Markov
[Termes IGN] classification dirigée
[Termes IGN] classification spectrale
[Termes IGN] image à haute résolution
[Termes IGN] image hyperspectrale
[Termes IGN] pouvoir de résolution spectrale
[Termes IGN] redondance de données
[Termes IGN] signature spectraleRésumé : (Auteur) High spectral resolution brings hyperspectral images with large amounts of information, which makes these images more useful in many applications than images obtained from traditional multispectral scanners with low spectral resolution. However, the high data dimensionality of hyperspectral images increases the burden on data computation, storage, and transmission; fortunately, the high redundancy in the spectral domain allows for significant dimensionality reduction. Band selection provides a simple dimensionality reduction scheme by discarding bands that are highly redundant, thereby preserving the structure of the data set. This paper proposes a new criterion for pointwise-ranking-based band selection that uses a nonhomogeneous hidden Markov chain (NHMC) model for redundant wavelet coefficients of each hyperspectral signature. The model provides a binary multiscale label that encodes semantic features that are useful to discriminate spectral types. A band ranking score considers the average correlation among the average NHMC labels for each band. We also test richer discrete-valued label vectors that provide a more finely grained quantization of spectral fluctuations. In addition, since band selection methods based on band ranking often ignore correlations in selected bands, we study the effect of redundancy elimination, applied on the selected features, on the performance of an example classification problem. Our experimental results also include an optional redundancy elimination step and test their effect on classification performance that is based on the selected bands. The experimental results also include a comparison with several relevant supervised band selection techniques. Numéro de notice : A2017-172 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2636850 En ligne : https://doi.org/10.1109/TGRS.2016.2636850 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84717
in IEEE Transactions on geoscience and remote sensing > vol 55 n° 4 (April 2017) . - pp 2111 - 2123[article]Multilayer NMF for blind unmixing of hyperspectral imagery with additional constraints / L. Chen in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 4 (April 2017)
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Titre : Multilayer NMF for blind unmixing of hyperspectral imagery with additional constraints Type de document : Article/Communication Auteurs : L. Chen, Auteur ; Shengbo Chen, Auteur ; Xulin Guo, Auteur Année de publication : 2017 Article en page(s) : pp 307 - 316 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] calcul matriciel
[Termes IGN] contrainte spectrale
[Termes IGN] factorisation de matrice non-négative
[Termes IGN] filtrage du bruit
[Termes IGN] image hyperspectrale
[Termes IGN] processus de hiérarchisation analytique
[Termes IGN] programmation par contraintes
[Termes IGN] réflectanceRésumé : (Auteur) Due to the coincidence of hyperspectral reflectance nonnegativity (and its corresponding abundance) with nonnegative matrix factorization (NMF) methods, NMF has been widely applied to unmix hyperspectral images in recent years. However, many local minima persist because of the nonconvexity of the objective function. Thus, the nonnegativity constraint is not sufficient and additional auxiliary constraints should be applied to objective functions. In this paper, a new approach we call constrained multilayer NMF (CMLNMF), is proposed for hyperspectral data. In this approach, the mixed spectra are regarded as endmember signatures that has been contaminated by multiplicative noise. The purpose of CMLNMF is to eliminate noise by hierarchical processing until the endmember spectra are obtained. Also, the hierarchical processing is self-adaptive to make the algorithm more effective. Furthermore, in each layer two constraints are implemented on the objective function. One is sparseness on the abundance matrix and the other is minimum volume on the spectral matrix. The hierarchical processing separates the abundance matrix into a series of matrices that make the characteristic of sparseness more obvious and meaningful. The proposed algorithm is applied to synthetic data and real hyperspectral data for quantitative evaluation. According to the comparison with other algorithms, CMLNMF has better performance and provides effective solutions for blind unmixing of hyperspectral image data. Numéro de notice : A2017-112 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE/MATHEMATIQUE Nature : Article DOI : 10.14358/PERS.83.4.307 En ligne : https://doi.org/10.14358/PERS.83.4.307 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84590
in Photogrammetric Engineering & Remote Sensing, PERS > vol 83 n° 4 (April 2017) . - pp 307 - 316[article]Semantic segmentation of forest stands of pure species combining airborne lidar data and very high resolution multispectral imagery / Clément Dechesne in ISPRS Journal of photogrammetry and remote sensing, vol 126 (April 2017)
[article]
Titre : Semantic segmentation of forest stands of pure species combining airborne lidar data and very high resolution multispectral imagery Type de document : Article/Communication Auteurs : Clément Dechesne , Auteur ; Clément Mallet , Auteur ; Arnaud Le Bris , Auteur ; Valérie Gouet-Brunet , Auteur Année de publication : 2017 Projets : HYEP / Weber, Christiane Article en page(s) : pp 129 – 145 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] classification automatique
[Termes IGN] classification dirigée
[Termes IGN] délimitation
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] espèce végétale
[Termes IGN] extraction d'arbres
[Termes IGN] fusion d'images
[Termes IGN] image aérienne
[Termes IGN] image multibande
[Termes IGN] peuplement forestier
[Termes IGN] segmentation sémantique
[Termes IGN] semis de pointsRésumé : (auteur) Forest stands are the basic units for forest inventory and mapping. Stands are defined as large forested areas (e.g., ⩾⩾2 ha) of homogeneous tree species composition and age. Their accurate delineation is usually performed by human operators through visual analysis of very high resolution (VHR) infra-red images. This task is tedious, highly time consuming, and should be automated for scalability and efficient updating purposes. In this paper, a method based on the fusion of airborne lidar data and VHR multispectral images is proposed for the automatic delineation of forest stands containing one dominant species (purity superior to 75%). This is the key preliminary task for forest land-cover database update. The multispectral images give information about the tree species whereas 3D lidar point clouds provide geometric information on the trees and allow their individual extraction. Multi-modal features are computed, both at pixel and object levels: the objects are individual trees extracted from lidar data. A supervised classification is then performed at the object level in order to coarsely discriminate the existing tree species in each area of interest. The classification results are further processed to obtain homogeneous areas with smooth borders by employing an energy minimum framework, where additional constraints are joined to form the energy function. The experimental results show that the proposed method provides very satisfactory results both in terms of stand labeling and delineation (overall accuracy ranges between 84% and 99%). Numéro de notice : A2017-116 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : FORET/IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.02.011 Date de publication en ligne : 27/02/2017 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2017.02.011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84511
in ISPRS Journal of photogrammetry and remote sensing > vol 126 (April 2017) . - pp 129 – 145[article]Réservation
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