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Uncertainty management for robust probabilistic change detection from multi-temporal Geoeye-1 imagery / Mahmoud Salah in Applied geomatics, vol 13 n° 2 (June 2021)  

Public [article]  inApplied geomatics > vol 13 n° 2 (June 2021) . - pp 261 - 275 Titre : Uncertainty management for robust probabilistic change detection from multi-temporal Geoeye-1 imagery Type de document : Article/Communication Auteurs : Mahmoud Salah, Auteur Année de publication : 2021 Article en page(s) : pp 261 - 275 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] appariement d'histogramme [Termes IGN] champ aléatoire de Markov [Termes IGN] classification dirigée [Termes IGN] classification par maximum de vraisemblance [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] détection de changement [Termes IGN] géoréférencement [Termes IGN] Giza [Termes IGN] image à très haute résolution [Termes IGN] image Geoeye [Termes IGN] image multitemporelle [Termes IGN] incertitude des données [Termes IGN] méthode robuste [Termes IGN] modèle de Markov caché [Termes IGN] occupation du sol [Termes IGN] réseau neuronal artificiel [Termes IGN] utilisation du sol Résumé : (auteur) Robust approaches for image change detection (ICD) are essential for a range of large-scale applications. However, the uncertainties involved in such approaches have not been fully addressed. To investigate this problem, this paper proposes a new approach for change detection from multi-temporal very high resolution (VHR) satellite imagery based on uncertainty detection and management. First, two GeoEye-1 images of Giza urban area (Egypt), acquired in 2009 and 2019, have been geographically co-registered and their histograms have been matched. Second, a set of feature attributes have been generated from the co-registered images. Third, the support vector machine (SVM) algorithm has been adopted to classify the data into four classes: building, tree, road, and ground. In this regard, the co-registered images along with the generated attributes have been applied as input data for the SVM to calculate the probability of each pixel belonging to each class. After that, the probability images for both epochs have been compared to model the uncertainty of changes. The uncertainty places are then evaluated to estimate their likelihood of being change or no change. Finally, the obtained results have been compared with manually digitized change detection map. Compared with using the widely used post-classification comparison (PCC) approach, the results suggest that (1) the proposed method has improved the overall accuracy of change detection by 13%; (2) the class-accuracies have been improved by 35.63%; and (3) the achieved accuracies for the proposed approach are less variable. Whereas the standard deviation (SD) of the accuracies obtained for the proposed approach is 6.80, the SD of those obtained for the PCC approach is 35.50. Numéro de notice : A2021-412 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s12518-020-00346-z Date de publication en ligne : 28/10/2020 En ligne : https://doi.org/10.1007/s12518-020-00346-z Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97737 [article]

Estimating forest stand density and structure using Bayesian individual tree detection, stochastic geometry, and distribution matching / Kasper Kansanen in ISPRS Journal of photogrammetry and remote sensing, vol 152 (June 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 152 (June 2019) . - pp 66 - 78 Titre : Estimating forest stand density and structure using Bayesian individual tree detection, stochastic geometry, and distribution matching Type de document : Article/Communication Auteurs : Kasper Kansanen, Auteur ; Jari Vauhkonen, Auteur ; Timo Lähivaara, Auteur ; Aku Seppänen, Auteur ; Matti Maltamo, Auteur ; Lauri Mehtätalo, Auteur Année de publication : 2019 Article en page(s) : pp 66 - 78 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] appariement d'histogramme [Termes IGN] chaîne de traitement [Termes IGN] détection d'arbres [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] Finlande [Termes IGN] forêt boréale [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] inventaire forestier local [Termes IGN] Picea abies [Termes IGN] Pinus sylvestris [Termes IGN] placette d'échantillonnage [Termes IGN] surface terrière [Vedettes matières IGN] Inventaire forestier Résumé : (Auteur) Errors in individual tree detection and delineation affect diameter distribution predictions based on crown attributes extracted from the detected trees. We develop a methodology for circumventing these problems. The method is based on matching cumulative distribution functions of field measured tree diameter distributions and crown radii distributions extracted from airborne laser scanning data through individual tree detection presented by Vauhkonen and Mehtätalo (2015). In this study, empirical distribution functions and a monotonic, nonlinear model curve are introduced. Tree crown radius distribution produced by individual tree detection is corrected by a method taking into account that all trees cannot be detected. The evaluation is based on the ability of the developed model sequence to predict quadratic mean diameter and total basal area. The studied data consists of 36 field plots in a typical boreal managed forest area in eastern Finland. The suggested enhancements to the model sequence produce improved results in most of the test cases. Most notably, in leave-one-out cross-validation experiments the modified models improve RMSE of basal area 13% in the full data and RMSE of quadratic mean diameter and basal area 69% and 11%, respectively, in pure pine plots. Better modeling of the crown radius distribution and improved matching between crown radii and stem diameters add the operational premises of the full distribution matching. Numéro de notice : A2019-455 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.04.007 Date de publication en ligne : 15/04/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.04.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92868 [article]

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More surface detail with one-two-pixel matching / Ewelina Rupnik (2019)    

Public Titre : More surface detail with one-two-pixel matching Type de document : Rapport Auteurs : Ewelina Rupnik , Auteur ; Marc Pierrot-Deseilligny , Auteur Editeur : Saint-Mandé : Institut national de l'information géographique et forestière - IGN Année de publication : 2019 Importance : 16 p. Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] appariement d'histogramme [Termes IGN] appariement de points [Termes IGN] appariement semi-global [Termes IGN] corrélation croisée normalisée [Termes IGN] corrélation par régions de niveaux de gris [Termes IGN] géosciences [Termes IGN] image captée par drone [Termes IGN] image Pléiades [Termes IGN] image SPOT 7 [Termes IGN] image terrestre [Termes IGN] MicMac [Termes IGN] modèle numérique de surface Résumé : (Auteur) Photogrammetrically derived Digital Surface Models have been widely adopted in geoscientific applications such as mapping and change detection across volcanic surfaces, glaciers, areas of seismic activity, forests, river landforms etc. Resolution of the reconstructed surface is crucial as more accurate information enables more profound understanding of the phenomena. With this objective in mind, the research presented here proposes a new matching cost function that produces surfaces of enhanced resolution with respect to the gold standard: the window-based semi-global matching technique. We evaluate the algorithm on different image datasets spanning various acquisition geometries, radiometric qualities and ground sample distance sizes. In particular , results on Earth satellites (SPOT-7, Pléiades), extraterres-trial (Chang'E3 moon landing), aerial and terrestrial acquisitions are shown. The implementation of the method is available in MicMac-the free open-source software for photogrammetry. I. INTRODUCTION Digital surface model (DSM or photogrammetric DSM) generation using dense image matching is an accepted technique across the geoscience communities. Next to other competitive techniques such as LiDAR or radar, image-based reconstruction produces denser 3D information, it is cost-effective and richer as it includes photometric observations that allow, for example, 3D change detection or classification. Photogrammetric DSMs in geoscience applications can be generated from terrestrial images, unmanned aerial vehicle (UAV) acquisitions or high-resolution optical satellite imaging. a) Terrestrial and UAV applications: Modelling of surface roughness parameters [1]; mapping volcanic surfaces [2]; and measuring glaciers' microrelief progression [3] are some of many examples of terrestrial applications carried out with consumer grade cameras and little expert knowledge. UAV-based surveys are increasingly presented as an alternative to terrestrial surveys due to their larger reach, their ease of deployment and reduced operational cost. With respect to resolution, UAV surveys are a compromise between high-resolution close-range and moderate-resolution satellite imaging. The success of the UAV technology is reflected in numerous publications which show that UAV-collected imagery can: enable modelling of forest canopy height [4]; determine the rate and extent of landslide movements [5]; quantify coastal erosion [6], [7] and deposition processes [8] in aeolian research; map ultrafine (i.e. centimetric) tectonic faults in tectonic research [9]; or be employed in repeated surveys of the ice-sheet masses in glaciology [10]. b) Earth satellite and extraterrestrial applications: With the available optical satellite data provided by modern (e.g. Pléiades 1A/B, SPOT-satellites, QuickBird, WorldView 2/3/4, CubeSat) or older satellites (e.g. CartoSat, ASTER), we can Numéro de notice : 26221 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : IMAGERIE Nature : Rapport de recherche nature-HAL : RappRech DOI : sans En ligne : https://hal.archives-ouvertes.fr/hal-02371337 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94223

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Intersensor statistical matching for pansharpening : theoretical issues and practical solutions / Luciano Alparone in IEEE Transactions on geoscience and remote sensing, vol 55 n° 8 (August 2017)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 55 n° 8 (August 2017) . - pp 4682 - 4695 Titre : Intersensor statistical matching for pansharpening : theoretical issues and practical solutions Type de document : Article/Communication Auteurs : Luciano Alparone, Auteur ; Andrea Garzelli, Auteur ; Gemine Vivone, Auteur Année de publication : 2017 Article en page(s) : pp 4682 - 4695 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte [Termes IGN] appariement d'histogramme [Termes IGN] appariement d'images [Termes IGN] image Ikonos [Termes IGN] image multibande [Termes IGN] image multicapteur [Termes IGN] image panchromatique [Termes IGN] image Worldview [Termes IGN] pansharpening (fusion d'images) [Termes IGN] résolution multiple Résumé : (Auteur) In this paper, the authors investigate the statistical matching of the panchromatic (Pan) image to the multispectral (MS) bands, also known as the histogram matching, for the two main classes of pansharpening methods, i.e., those based on component substitution (CS) or spectral methods and those based on multiresolution analysis (MRA) or spatial methods. Also, hybrid methods combining CS with MRA, like the widespread additive wavelet luminance proportional (AWLP), are investigated. It is shown that all spectral, spatial, and hybrid methods must perform a dynamics matching of the enhancing Pan to the individual MS bands for MRA or a combination of them (the component that shall be substituted) for CS. For hybrid methods, the problem is more complex and both types of histogram matching may be suitable. Such an intersensor balance may be either explicit or implicitly performed by the detail-injection model, e.g., the popular projective and multiplicative injection models. An experimental setup exploiting IKONOS and WorldView-2 data sets demonstrates that a correct histogram matching is the key to attain extra performance from established methods. As a first result of this paper, the AWLP method has been revisited and its performance significantly improved by simply performing the histogram matching of Pan to the individual MS bands, rather than to the intensity component, thereby losing the original proportionality feature. Numéro de notice : A2017-502 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2017.2697943 En ligne : http://dx.doi.org/10.1109/TGRS.2017.2697943 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86447 [article]

A GIHS-based spectral preservation fusion method for remote sensing images using edge restored spectral modulation / Xiran Zhou in ISPRS Journal of photogrammetry and remote sensing, vol 88 (February 2014)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 88 (February 2014) . - pp 16 - 27 Titre : A GIHS-based spectral preservation fusion method for remote sensing images using edge restored spectral modulation Type de document : Article/Communication Auteurs : Xiran Zhou, Auteur ; Jun Liu, Auteur ; Lei Cao, Auteur ; Qiming Zhou, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 16 - 27 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] algorithme de fusion [Termes IGN] appariement d'histogramme [Termes IGN] filtrage numérique d'image [Termes IGN] fusion d'images [Termes IGN] image multibande [Termes IGN] modulation de fréquence [Termes IGN] qualité d'image [Termes IGN] transformation intensité-teinte-saturation Résumé : (Auteur) High spatial resolution and spectral fidelity are basic standards for evaluating an image fusion algorithm. Numerous fusion methods for remote sensing images have been developed. Some of these methods are based on the intensity–hue–saturation (IHS) transform and the generalized IHS (GIHS), which may cause serious spectral distortion. Spectral distortion in the GIHS is proven to result from changes in saturation during fusion. Therefore, reducing such changes can achieve high spectral fidelity. A GIHS-based spectral preservation fusion method that can theoretically reduce spectral distortion is proposed in this study. The proposed algorithm consists of two steps. The first step is spectral modulation (SM), which uses the Gaussian function to extract spatial details and conduct SM of multispectral (MS) images. This method yields a desirable visual effect without requiring histogram matching between the panchromatic image and the intensity of the MS image. The second step uses the Gaussian convolution function to restore lost edge details during SM. The proposed method is proven effective and shown to provide better results compared with other GIHS-based methods. Numéro de notice : A2014-081 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.11.011 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.11.011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32986 [article]

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Remote sensing image segmentation by combining spectral and texture features / H. Li in IEEE Transactions on geoscience and remote sensing, vol 52 n° 1 tome 1 (January 2014)  

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Histogram curve matching approaches for object-based image classification of land cover and land use / Sory I. Toure in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 5 (May 2013)  

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Cloud-free satellite image mosaics with regression trees and histogram matching / E.H. Helmert in Photogrammetric Engineering & Remote Sensing, PERS, vol 71 n° 9 (September 2005)  

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Topographic information of sand dunes as extracted from shading effects using Landsat images / N. Levin in Remote sensing of environment, vol 90 n° 2 (30/03/2004)  

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True orthophoto generation of built-up areas using multi-view images / J.Y. Rau in Photogrammetric Engineering & Remote Sensing, PERS, vol 68 n° 6 (June 2002)

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Destriping multiple sensor imagery by improved histogram matching / M. Wegener in International Journal of Remote Sensing IJRS, vol 11 n° 5 (May 1990)  

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