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Shadow detection in very high spatial resolution aerial images: A comparative study / Karine R.M. Adeline in ISPRS Journal of photogrammetry and remote sensing, vol 80 (June 2013)
[article]
Titre : Shadow detection in very high spatial resolution aerial images: A comparative study Type de document : Article/Communication Auteurs : Karine R.M. Adeline, Auteur ; M. Chen, Auteur ; Xavier Briottet , Auteur ; S.K. Pan, Auteur ; Nicolas Paparoditis , Auteur Année de publication : 2013 Article en page(s) : pp 21 - 38 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] canyon urbain
[Termes IGN] détection d'ombre
[Termes IGN] image hyperspectrale
[Termes IGN] image multibande
[Termes IGN] rayonnement lumineux
[Termes IGN] rayonnement proche infrarouge
[Termes IGN] seuillage d'image
[Termes IGN] simulation numérique
[Termes IGN] test de performanceRésumé : (Auteur) Automatic shadow detection is a very important pre-processing step for many remote sensing applications, particularly for images acquired with high spatial resolution. In complex urban environments, shadows may occupy a significant portion of the image. Ignoring these regions would lead to errors in various applications, such as atmospheric correction and classification. To better understand the radiative impact of shadows, a physical study was conducted through the simulation of a synthetic urban canyon scene. Its results helped to explain the most common assumptions made on shadows from a physical point of view in the literature. With this understanding, state-of-the-art methods on shadow detection were surveyed and categorized into six classes: histogram thresholding, invariant color models, object segmentation, geometrical methods, physics-based methods, unsupervised and supervised machine learning methods. Among them, some methods were selected and tested on a large dataset of multispectral and hyperspectral airborne images with high spatial resolution. The dataset chosen contains a large variety of typical occidental urban scenes. The results were compared based on accurate reference shadow masks. In these experiments, histogram thresholding on RGB and NIR channels performed the best with an average accuracy of 92.5%, followed by physics-based methods, such as Richter’s method with 90.0%. Finally, this paper analyzes and discusses the limits of these algorithms, concluding with some recommendations for shadow detection. Numéro de notice : A2013-296 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.02.003 Date de publication en ligne : 03/04/2013 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2013.02.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32434
in ISPRS Journal of photogrammetry and remote sensing > vol 80 (June 2013) . - pp 21 - 38[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2013061 RAB Revue Centre de documentation En réserve L003 Disponible Texture augmented detection of macrophyte species using decision trees / Cameron Proctor in ISPRS Journal of photogrammetry and remote sensing, vol 80 (June 2013)
[article]
Titre : Texture augmented detection of macrophyte species using decision trees Type de document : Article/Communication Auteurs : Cameron Proctor, Auteur ; Yuhong He, Auteur ; Vincent Robinson, Auteur Année de publication : 2013 Article en page(s) : pp 10 - 20 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] algue
[Termes IGN] classification par arbre de décision
[Termes IGN] image panchromatique
[Termes IGN] image Quickbird
[Termes IGN] macrophyte
[Termes IGN] précision de la classification
[Termes IGN] rivière
[Termes IGN] séparabilité
[Termes IGN] texture d'imageRésumé : (Auteur) Image classification using multispectral sensors has shown good performance in detecting macrophytes at the species level. However, species level classification often does not utilize the texture information provided by high resolution images. This study investigated whether image texture provides useful vector(s) for the discrimination of monospecific stands of three floating macrophyte species in Quickbird imagery of the South Nation River. Semivariograms indicated that window sizes of 5 x 5 and 13 x 13 pixels were the most appropriate spatial scales for calculation of the grey level co-occurrence matrix and subsequent texture attributes from the multispectral and panchromatic bands. Of the 214 investigated vectors (13 Haralick texture attributes * 15 bands + 9 spectral bands + 10 transformations/indices), feature selection determined which combination of spectral and textural vectors had the greatest class separability based on the Mann–Whitney U-test and Jefferies–Matusita distance. While multispectral red and near infrared (NIR) performed satisfactorily, the addition of panchromatic-dissimilarity slightly improved class separability and the accuracy of a decision tree classifier (Kappa: red/NIR/panchromatic-dissimilarity – 93.2% versus red/NIR – 90.4%). Class separability improved by incorporating a second texture attribute, but resulted in a decrease in classification accuracy. The results suggest that incorporating image texture may be beneficial for separating stands with high spatial heterogeneity. However, the benefits may be limited and must be weighed against the increased complexity of the classifier. Numéro de notice : A2013-295 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.02.022 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.02.022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32433
in ISPRS Journal of photogrammetry and remote sensing > vol 80 (June 2013) . - pp 10 - 20[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2013061 RAB Revue Centre de documentation En réserve L003 Disponible Attraction-repulsion model-based subpixel mapping of multi-/hyperspectral imagery / Xiaohua Tong in IEEE Transactions on geoscience and remote sensing, vol 51 n° 5 Tome 1 (May 2013)
[article]
Titre : Attraction-repulsion model-based subpixel mapping of multi-/hyperspectral imagery Type de document : Article/Communication Auteurs : Xiaohua Tong, Auteur ; Xue Zhang, Auteur ; Jie Shan, Auteur ; et al., Auteur Année de publication : 2013 Article en page(s) : pp 2799 - 2814 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] affinage d'image
[Termes IGN] analyse infrapixellaire
[Termes IGN] décomposition du pixel
[Termes IGN] image EO1-Hyperion
[Termes IGN] image hyperspectrale
[Termes IGN] programmation linéaire
[Termes IGN] reconstruction d'imageRésumé : (Auteur) This paper presents a new subpixel mapping method based on subpixel attraction-repulsion. The proposed method is formulated as an optimization problem with respect to attraction-repulsion among subpixels and is used to reconstruct a finer spatial resolution image from a lower resolution one. A comprehensive experiment is conducted to demonstrate the performance of the proposed method, by comparing it with the other three existing subpixel mapping methods, i.e., linear optimization, pixel swapping and spatial attraction model methods. In the experiment, both a synthetic image with known fractional abundances and an EO-1 Hyperion hyperspectral image of Shanghai were used to evaluate performances of the subpixel mapping methods. The experimental result shows that by using spatial dependence with attraction between the same types of ground objects and repulsion between different types of these objects, the proposed subpixel mapping method achieves a better performance on subpixel mapping than the other three methods Numéro de notice : A2013-257 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2218612 En ligne : https://doi.org/10.1109/TGRS.2012.2218612 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32395
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 5 Tome 1 (May 2013) . - pp 2799 - 2814[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2013051A RAB Revue Centre de documentation En réserve L003 Disponible Change detection and deformation analysis in point clouds: Application to rock face monitoring / Marco Scaioni in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 5 (May 2013)
[article]
Titre : Change detection and deformation analysis in point clouds: Application to rock face monitoring Type de document : Article/Communication Auteurs : Marco Scaioni, Auteur ; Riccardo Roncella, Auteur ; Mario Ivan Alba, Auteur Année de publication : 2013 Article en page(s) : pp 441 - 455 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] analyse comparative
[Termes IGN] analyse diachronique
[Termes IGN] détection de changement
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] éboulement
[Termes IGN] falaise
[Termes IGN] filtrage de la végétation
[Termes IGN] image RVB
[Termes IGN] Italie
[Termes IGN] montagne
[Termes IGN] Préalpes (Europe)
[Termes IGN] semis de points
[Termes IGN] télémétrie laser terrestreRésumé : (Auteur) The paper outlines a method to compare two digital surfaces of the same rock face to detect major changes resulting from detached rocks and deformations. A terrestrial laser scanning survey is used for data gathering. After georeferencing, if the cliff has a complex morphology, a 3D segmentation algorithm is applied to split the whole rock surface into more subregions with an almost planar structure. In each subregion the raw point cloud is resampled on a regular grid and multitemporal differences are analyzed. Anomalies in differences, which should be very close to zero if no geometric variations have occurred, are identified with the following purposes: (a) localizing gross changes due to rock detachments, (b) removing global rigid-body displacements, and (c) understanding local cliff deformations. In the case where the rock face is covered by vegetation, this has to be filtered out, e.g., by visual inspection of RGB images co-registered to the point cloud. This paper also describes a procedure to carry out vegetation filtering in automatic way from the analysis of near-infrared images captured by a camera integrated to laser scanner. The application of the full processing pipeline has been tested on a real case study located in the Italian pre-alpine area. Here, after filtering some vegetation, a total rock fall volume of 0.15 m3 was detected on a cliff of about 375 m2 and within a period of six months. Numéro de notice : A2013-282 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.79.5.441 En ligne : https://doi.org/10.14358/PERS.79.5.441 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32420
in Photogrammetric Engineering & Remote Sensing, PERS > vol 79 n° 5 (May 2013) . - pp 441 - 455[article]A classification algorithm for hyperspectral images based on synergetics theory / Daniele Cerra in IEEE Transactions on geoscience and remote sensing, vol 51 n° 5 Tome 1 (May 2013)
[article]
Titre : A classification algorithm for hyperspectral images based on synergetics theory Type de document : Article/Communication Auteurs : Daniele Cerra, Auteur ; Rupert Müller, Auteur ; Peter Reinartz, Auteur Année de publication : 2013 Article en page(s) : pp 2887 - 2898 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse d'image numérique
[Termes IGN] classification
[Termes IGN] image hyperspectraleRésumé : (Auteur) This paper presents a classification methodology for hyperspectral data based on synergetics theory. Pattern recognition algorithms based on synergetics have been applied to images in the spatial domain with limited success in the past, given their dependence on the rotation, shifting, and scaling of the images. These drawbacks can be discarded if such methods are applied to data acquired by a hyperspectral sensor in the spectral domain, as each single spectrum, related to an image element in the hyperspectral scene, can be analyzed independently. The spectrum is first projected in a space spanned by a set of user-defined prototype vectors, which belong to some classes of interest, and then attracted by a final state associated to a prototype. The spectrum can thus be classified, establishing a first attempt at performing a pixel-wise image classification using notions derived from synergetics. As typical synergetics-based systems have the drawback of a rigid training step, we introduce a new procedure which allows the selection of a training area for each class of interest, used to weight the prototype vectors through attention parameters and to produce a more accurate classification map through plurality vote of independent classifications. As each classification is in principle obtained on the basis of a single training sample per class, the proposed technique could be particularly effective in tasks where only a small training data set is available. The results presented are promising and often outperform state-of-the-art classification methodologies, both general and specific to hyperspectral data. Numéro de notice : A2013-269 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2219059 En ligne : https://doi.org/10.1109/TGRS.2012.2219059 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32407
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 5 Tome 1 (May 2013) . - pp 2887 - 2898[article]Réservation
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