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Slow feature analysis for change detection in multispectral imagery / Chen Wu in IEEE Transactions on geoscience and remote sensing, vol 52 n° 5 tome 1 (May 2014)
[article]
Titre : Slow feature analysis for change detection in multispectral imagery Type de document : Article/Communication Auteurs : Chen Wu, Auteur ; Bo Du, Auteur ; Liangpei Zhang, Auteur Année de publication : 2014 Article en page(s) : pp 2858 - 2874 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse de variance
[Termes IGN] détection de changement
[Termes IGN] image Landsat-ETM+
[Termes IGN] image multibande
[Termes IGN] image multitemporelle
[Termes IGN] pixel
[Termes IGN] varianceRésumé : (Auteur) Change detection was one of the earliest and is also one of the most important applications of remote sensing technology. For multispectral images, an effective solution for the change detection problem is to exploit all the available spectral bands to detect the spectral changes. However, in practice, the temporal spectral variance makes it difficult to separate changes and nonchanges. In this paper, we propose a novel slow feature analysis (SFA) algorithm for change detection. Compared with changed pixels, the unchanged ones should be spectrally invariant and varying slowly across the multitemporal images. SFA extracts the most temporally invariant component from the multitemporal images to transform the data into a new feature space. In this feature space, the differences in the unchanged pixels are suppressed so that the changed pixels can be better separated. Three SFA change detection approaches, comprising unsupervised SFA, supervised SFA, and iterative SFA, are constructed. Experiments on two groups of real Enhanced Thematic Mapper data sets show that our proposed method performs better in detecting changes than the other state-of-the-art change detection methods. Numéro de notice : A2014-264 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2266673 En ligne : https://doi.org/10.1109/TGRS.2013.2266673 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=33167
in IEEE Transactions on geoscience and remote sensing > vol 52 n° 5 tome 1 (May 2014) . - pp 2858 - 2874[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2014051A RAB Revue Centre de documentation En réserve L003 En circulation
Exclu du prêtSupervised change detection in satellite imagery using super pixels and relevance feedback / Surender Varma Gadhiraju in Geomatica, vol 68 n° 1 (March 2014)
[article]
Titre : Supervised change detection in satellite imagery using super pixels and relevance feedback Type de document : Article/Communication Auteurs : Surender Varma Gadhiraju, Auteur ; Hichem Sahbi, Auteur ; Biplab Banerjee, Auteur ; Krishna Mohan Buddhiraju, Auteur Année de publication : 2014 Article en page(s) : pp 5 - 14 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse comparative
[Termes IGN] classificateur paramétrique
[Termes IGN] classification dirigée
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] détection de changement
[Termes IGN] données de terrain
[Termes IGN] image multitemporelle
[Termes IGN] pertinence
[Termes IGN] pixelRésumé : (auteur) Les données provenant des satellites de télédétection offrent la possibilité de recueillir de l’information au sujet des terres selon diverses résolutions et ont été largement utilisées dans le cadre des études de détection de changements. Un grand nombre de méthodologies et de techniques de détection de changements utilisant les données de télédétection ont été développées et de nouvelles techniques font encore leur apparition. Dans le présent article, nous proposons une nouvelle approche supervisée de détection de changements qui utilise une Machine à vecteurs de support (SVM) et des super pixels. Dans la formulation de la détection de changements, les SVM sont modélisés comme un classificateur binaire afin d’obtenir l’extrant final « Changement » et « Pas de changement » comme information. Un mécanisme de contrôle de pertinence est également inclus dans la stratégie de détection de changements de façon à ce qu’elle s’adapte aux préférences de l’utilisateur. La réalité de terrain et le contrôle de pertinence sont tous deux collectés en utilisant les IUG développés. Une comparaison de l’approche proposée avec trois autres techniques de détection de changements est effectuée au moyen des expériences réalisées sur trois jeux de données multitemporelles. On observe que la stratégie de détection de changements supervisée et axée sur les super pixels donne des résultats supérieurs comparativement aux approches traditionnelles de détection de changements. On observe également que l’utilisation du contrôle de pertinence affine les résultats de la détection de changements et agit comme un processus souhaitable de suivi de la détection de changements. Numéro de notice : A2014-666 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.5623/cig2014-001 En ligne : https://doi.org/10.5623/cig2014-001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75354
in Geomatica > vol 68 n° 1 (March 2014) . - pp 5 - 14[article]Assessment of the image misregistration effects on object-based change detection / Gang Chen in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)
[article]
Titre : Assessment of the image misregistration effects on object-based change detection Type de document : Article/Communication Auteurs : Gang Chen, Auteur ; Kaiguang Zhao, Auteur ; Ryan Powers, Auteur Année de publication : 2014 Article en page(s) : pp 19 - 27 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse diachronique
[Termes IGN] classification orientée objet
[Termes IGN] détection de changement
[Termes IGN] estimation de précision
[Termes IGN] image multitemporelle
[Termes IGN] image SPOT 5Résumé : (Auteur) High-spatial resolution remote sensing imagery provides unique opportunities for detailed characterization and monitoring of landscape dynamics. To better handle such data sets, change detection using the object-based paradigm, i.e., object-based change detection (OBCD), have demonstrated improved performances over the classic pixel-based paradigm. However, image registration remains a critical pre-process, with new challenges arising, because objects in OBCD are of various sizes and shapes. In this study, we quantified the effects of misregistration on OBCD using high-spatial resolution SPOT 5 imagery (5 m) for three types of landscapes dominated by urban, suburban and rural features, representing diverse geographic objects. The experiments were conducted in four steps: (i) Images were purposely shifted to simulate the misregistration effect. (ii) Image differencing change detection was employed to generate difference images with all the image-objects projected to a feature space consisting of both spectral and texture variables. (iii) The changes were extracted using the Mahalanobis distance and a change ratio. (iv) The results were compared to the ‘real’ changes from the image pairs that contained no purposely introduced registration error. A pixel-based change detection method using similar steps was also developed for comparisons. Results indicate that misregistration had a relatively low impact on object size and shape for most areas. When the landscape is comprised of small mean object sizes (e.g., in urban and suburban areas), the mean size of ‘change’ objects was smaller than the mean of all objects and their size discrepancy became larger with the decrease in object size. Compared to the results using the pixel-based paradigm, OBCD was less sensitive to the misregistration effect, and the sensitivity further decreased with an increase in local mean object size. However, high-spatial resolution images typically have higher spectral variability within neighboring pixels than the relatively low resolution datasets. As a result, accurate image registration remains crucial to change detection even if an object-based approach is used. Numéro de notice : A2014-008 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.10.007 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.10.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32913
in ISPRS Journal of photogrammetry and remote sensing > vol 87 (January 2014) . - pp 19 - 27[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2014011 RAB Revue Centre de documentation En réserve L003 Disponible Patch-based information reconstruction of cloud-contaminated multitemporal images / Chao-Hung Lin in IEEE Transactions on geoscience and remote sensing, vol 52 n° 1 tome 1 (January 2014)
[article]
Titre : Patch-based information reconstruction of cloud-contaminated multitemporal images Type de document : Article/Communication Auteurs : Chao-Hung Lin, Auteur ; Kang-Hua Lai, Auteur ; Zhi-Bin Chen, Auteur ; Jyun-Yuan Chen, Auteur Année de publication : 2014 Article en page(s) : pp 163 - 174 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] cohérence (physique)
[Termes IGN] corrélation
[Termes IGN] image Landsat-ETM+
[Termes IGN] image multitemporelle
[Termes IGN] manteau neigeuxRésumé : (Auteur) Cloud covers, which are generally present in optical remote sensing images, limit the usage of acquired images and increase the difficulty in data analysis. Thus, information reconstruction of cloud-contaminated images generally plays an important role in image analysis. This paper proposes a novel method to reconstruct cloud-contaminated information in multitemporal remote sensing images. Based on the concept of utilizing temporal correlation of multitemporal images, we propose a patch-based information reconstruction algorithm that spatiotemporally segments a sequence of images into clusters containing several spatially connected components called patches and then clones information from cloud-free and high-similarity patches to their corresponding cloud-contaminated patches. In addition, a seam that passes through homogenous regions is used in information reconstruction to reduce radiometric inconsistency, and information cloning is solved using an optimization process with the determined seam. These processes enable the proposed method to well reconstruct missing information. Qualitative analyses of image sequences acquired by a Landsat-7 Enhanced Thematic Mapper Plus (ETM+) sensor and a quantitative analysis of simulated data with various cloud contamination conditions are conducted to evaluate the proposed method. The experimental results demonstrate the superiority of the proposed method to related methods in terms of radiometric accuracy and consistency, particularly for large clouds in a heterogeneous landscape. Numéro de notice : A2014-035 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2237408 En ligne : https://doi.org/10.1109/TGRS.2012.2237408 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32940
in IEEE Transactions on geoscience and remote sensing > vol 52 n° 1 tome 1 (January 2014) . - pp 163 - 174[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2014011A RAB Revue Centre de documentation En réserve L003 Disponible Markov land cover change modeling using pairs of time-series satellite images / Priyakant Sinha in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 11 (November 2013)
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Titre : Markov land cover change modeling using pairs of time-series satellite images Type de document : Article/Communication Auteurs : Priyakant Sinha, Auteur ; Lalit Kumar, Auteur Année de publication : 2013 Article en page(s) : pp 1037 - 1051 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] automate cellulaire
[Termes IGN] chaîne de Markov
[Termes IGN] flore locale
[Termes IGN] image Landsat-MSS
[Termes IGN] image Landsat-TM
[Termes IGN] image multitemporelle
[Termes IGN] Nouvelle-Galles du Sud
[Termes IGN] occupation du sol
[Termes IGN] prédictionRésumé : (Auteur) Models of change processes created with the Markov chain model (MCM) can be used in the interpolation of temporal data and in short-term change projections. However, there are two major issues associated with the use of Markov models for land-cover change projections: the stationarity of change and the impact of neighboring cells on the change areas. This study addressed these two issues using an investigation of five time-series land-cover datasets generated between 1972 and 2009 for the Liverpool region of NSW, Australia. Four short- term transition matrices were computed, and the results were used to predict land-cover distributions for the near future. The issue of neighborhood effects was addressed by incorporating spatial components in a Cellular Automata (CA)-based MCM, and the results were compared with those derived from a normal MCM. Given the marginal improvements in the simulation achieved with CA-MCM rather than MCM, and because of the ability of CA-MCM to incorporate spatial variants, CA-MCM was determined to be the more suitable method for predicting land-cover changes for the year 2019. The land-cover projection indicated that future land-cover changes will likely continue to affect the natural vegetation, which will in turn likely decrease through the continued conversion of natural to agricultural lands over the years. Numéro de notice : A2013-598 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.79.11.1037 En ligne : https://doi.org/10.14358/PERS.79.11.1037 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32734
in Photogrammetric Engineering & Remote Sensing, PERS > vol 79 n° 11 (November 2013) . - pp 1037 - 1051[article]Modeling of spatio-temporal dynamics of land use and land cover in a part of Brahmaputra River basin using Geoinformatic techniques / M. Sarabuddin Mondal in Geocarto international, vol 28 n° 7-8 (November - December 2013)PermalinkLa télédétection au service des études urbaines : expansion de la ville de Pondichéry entre 1973 et 2009 / Emilien Kieffer in Géomatique expert, n° 95 (01/11/2013)PermalinkAutomated detection of slum area change in Hyderabad, India using multitemporal satellite imagery / Oleksandr Kit in ISPRS Journal of photogrammetry and remote sensing, vol 83 (September 2013)PermalinkLa combinaison d'indicateurs de changement pour le suivi de l'évolution de l'occupation du sol à partir d'imagerie satellitale / Faten Katlane in Revue Française de Photogrammétrie et de Télédétection, n° 203 (Juillet 2013)PermalinkLow altitude aerial photography applications for digital surface models creation in archaeology / José-Angel Martinez-Del-Pozo in Transactions in GIS, vol 17 n° 2 (April 2013)PermalinkObject-based fusion of multitemporal multiangle ENVISAT ASAR and HJ-1B multispectral data for urban land-cover mapping / Yifang Ban in IEEE Transactions on geoscience and remote sensing, vol 51 n° 4 Tome 1 (April 2013)PermalinkCrop yield estimation based on unsupervised linear unmixing of multidate hyperspectral imagery / B. Luo in IEEE Transactions on geoscience and remote sensing, vol 51 n° 1 Tome 1 (January 2013)PermalinkSuper-resolution image analysis as a means of monitoring bracken (Pteridium aquilinum) distributions / Jennie Holland in ISPRS Journal of photogrammetry and remote sensing, vol 75 (January 2013)PermalinkUpdating land-cover maps by classification of image time series : A novel change-detection-driven transfer learning approach / Begüm Demir in IEEE Transactions on geoscience and remote sensing, vol 51 n° 1 Tome 1 (January 2013)PermalinkCorrelation of multi-temporal ground-based optical images for landslide monitoring: Application, potential and limitations / J. Travelleti in ISPRS Journal of photogrammetry and remote sensing, vol 70 (June 2012)PermalinkA framework for automatic and unsupervised detection of multiple changes in multitemporal images / Francesca Bovolo in IEEE Transactions on geoscience and remote sensing, vol 50 n° 6 (June 2012)PermalinkRelative radiometric correction of multi-temporal ALOS AVNIR-2 data for the estimation of forest attributes / Q. Xu in ISPRS Journal of photogrammetry and remote sensing, vol 68 (March 2012)PermalinkAutomatic cloud detection from multi-temporal satellite images: towards the use of Pléiades time series / Nicolas Champion (2012)PermalinkDamage assessment of 2010 Haïti earthquake with post-earthquake satellite image by support vector selection and adaptation / Gülsen Taskin Kaya in Photogrammetric Engineering & Remote Sensing, PERS, vol 77 n° 10 (October 2011)PermalinkLand cover classification of cloud-contaminated multitemporal high-resolution images / A. Salberg in IEEE Transactions on geoscience and remote sensing, vol 49 n° 1 Tome 2 (January 2011)PermalinkLand use and land cover change detection using satellite remote sensing techniques in the mountainous Three Gorges Area, China / Z. Chen in International Journal of Remote Sensing IJRS, vol 31 n° 6 (March 2010)PermalinkInfluence of resolution in irrigated area mapping and area estimations / N. Velpuri in Photogrammetric Engineering & Remote Sensing, PERS, vol 75 n° 12 (December 2009)PermalinkEvaluating the temporal and spatial urban expansion patterns of Guangzhou from 1979 to 2003 by remote sensing and GIS methods / F. Fan in International journal of geographical information science IJGIS, vol 23 n°11-12 (november 2009)PermalinkA matching algorithm for detecting land use changes using case-based reasoning / X. Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 75 n° 11 (November 2009)PermalinkApplications of remote sensing and geographic information systems for urban land-cover change studies in Mongolia / D. Amarsaikhan in Geocarto international, vol 24 n° 4 (August - September 2009)PermalinkA disturbance inventory framework for flexible and reliable landscape monitoring / J. Linke in Photogrammetric Engineering & Remote Sensing, PERS, vol 75 n° 8 (August 2009)PermalinkAnalyse exploratoire des effets de support spatial et de robustesse statistique sur la fiabilité de la mesure de la (bio)diversité / Didier Josselin in Photo interprétation, European journal of applied remote sensing, vol 45 n° 1 (mars 2009)PermalinkFeature reduction using a singular value decomposition for the iterative guided spectral class rejection hybrid classifier / R. Philipps in ISPRS Journal of photogrammetry and remote sensing, vol 64 n° 1 (January - February 2009)PermalinkFuzzy inference guided cellular automata urban-growth modelling using multi-temporal satellite images / S. Al-Kheder in International journal of geographical information science IJGIS, vol 22 n°11-12 (november 2008)PermalinkEarthquake-induced landslide hazard monitoring and assessment using SOM and PROMETHEE techniques: a case study at the Chiufenershan area in Central Taiwan / W.T. Lin in International journal of geographical information science IJGIS, vol 22 n° 8-9 (august 2008)PermalinkUrban change detection based on coherence and intensity characteristics of SAR imagery / M. Liao in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 8 (August 2008)PermalinkEtude géomorphologique des coulées de lave du piton de la fournaise / Astrid Gladys (2008)PermalinkEarly fire detection using non-linear multi-temporal prediction of thermal imagery / A. Koltunov in Remote sensing of environment, vol 110 n° 1 (14/09/2007)PermalinkMultitemporel fuzzy classification model based on class transition possibilities / G.L.A. Mota in ISPRS Journal of photogrammetry and remote sensing, vol 62 n° 3 (August 2007)PermalinkRule-based classification of multi-temporal satellite imagery for habitat and agricultural land cover mapping / Robert Lucas in ISPRS Journal of photogrammetry and remote sensing, vol 62 n° 3 (August 2007)PermalinkActive forest monitoring in Uttaranchal state, India using multi-temporal DMSP-OLS and MODIS data / T.R. Kiranchand in International Journal of Remote Sensing IJRS, vol 28 n° 10 (May 2007)PermalinkARRSI: Automatic Registration of Remote-Sensing Images / A. Wong in IEEE Transactions on geoscience and remote sensing, vol 45 n° 5 Tome 2 (May 2007)PermalinkA new statistical similarity measure for change detection in multi-temporal SAR images and its extension to multi-scale change analysis / Jordi Inglada in IEEE Transactions on geoscience and remote sensing, vol 45 n° 5 Tome 2 (May 2007)PermalinkApport des données Spot et Landsat au suivi des inondations dans l'estuaire du fleuve Sénégal / A.M. Dia in Photo interprétation, vol 42 n° 4 (Décembre 2006)PermalinkAn extended cellular automaton using case-based reasoning for simulating urban development in a large complex region / X. Li in International journal of geographical information science IJGIS, vol 20 n° 10 (november 2006)PermalinkTemporal influences on Landsat-5 thematic image in visible band / Y. Liu in International Journal of Remote Sensing IJRS, vol 27 n°15-16 (August 2006)PermalinkAutomated techniques for environmental monitoring and change analyses for ultra high resolution remote sensing data / Manfred Ehlers in Photogrammetric Engineering & Remote Sensing, PERS, vol 72 n° 7 (July 2006)PermalinkStudy of tectonics in relation to the seismic activity of the Davalt area, Nasik district, Maharashtra, India using remote sensing and GIS techniques / J. Sarup in International Journal of Remote Sensing IJRS, vol 27 n°12-13-14 (July 2006)PermalinkContextual reconstruction of cloud-contaminated multitemporal multispectral image / F. Melgani in IEEE Transactions on geoscience and remote sensing, vol 44 n° 2 (February 2006)PermalinkApports de l'imagerie satellitaire à la mise à jour de l'information géographique dans les pays de la ceinture tropicale / J.L. Kouame (2006)PermalinkMapping submergent aquatic vegetation in the US Great Lakes using Quickbird satellite data / P.T. Wolter in International Journal of Remote Sensing IJRS, vol 26 n° 23 (December 2005)PermalinkA detail-preserving scale-driven approach to change detection in multitemporal SAR images / F. Bolovo in IEEE Transactions on geoscience and remote sensing, vol 43 n° 12 (December 2005)PermalinkClassifying and mapping wildfire severity: a comparison of methods / C.K. Brewer in Photogrammetric Engineering & Remote Sensing, PERS, vol 71 n° 11 (November 2005)PermalinkOn the relationship between training sample size data dimensionality: Monte Carlo analysis of broadland multi-temporal classification / T.G. Van Niel in Remote sensing of environment, vol 98 n° 4 (30/10/2005)PermalinkA simple and effective radiometric correction method to improve landscape change detection across sensors and across time / X. Chen in Remote sensing of environment, vol 98 n° 1 (30/09/2005)Permalink