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Spatial resolution improvement of remote sensing images by fusion of subpixel-shifted multi-observation images / Y. Lu in International Journal of Remote Sensing IJRS, vol 24 n° 23 (December 2003)
[article]
Titre : Spatial resolution improvement of remote sensing images by fusion of subpixel-shifted multi-observation images Type de document : Article/Communication Auteurs : Y. Lu, Auteur ; M. Inamura, Auteur Année de publication : 2003 Article en page(s) : pp 4647 - 4660 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] conflation
[Termes IGN] fusion d'images
[Termes IGN] image à haute résolution
[Termes IGN] image Landsat-TM
[Termes IGN] image multicapteur
[Termes IGN] limite de résolution géométrique
[Termes IGN] précision infrapixellaire
[Termes IGN] qualité géométrique (image)
[Termes IGN] résolution multipleRésumé : (Auteur) Multi-observation of satellite remote-sensing provides the ability to achieve a higher spatial resolution image. Based on the relation between sensors of different spatial resolution, this paper presents a multi-observation in spatial called subpixel-shifted multi-observation, to acquire a more accurate image of higher spatial resolution than the original observations. In this kind of observation, the same area on the ground is observed repeatedly with a spatial resolution in a subpixel shifted way. All the acquired observation images are combined into a higher resolution image. This formulated as a super-resolution equation. When comparing the existing super-resolution algorithms, we find that the Iterative Back-Projection (IBP) method suggested by Peleg et al. is an appropriate and effective method for solving this problem. Based on IBP, a pratical implementation is presented. Computer experiments on remote sensing images and error analysis show its effectiveness. Some problems, such as back projection, undersampling, and fusion of observed samples, are discussed further. The resultant image from this method has both better quality and higher spatial resolution than the original observation. Numéro de notice : A2003-311 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160310001595064 En ligne : https://doi.org/10.1080/01431160310001595064 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22607
in International Journal of Remote Sensing IJRS > vol 24 n° 23 (December 2003) . - pp 4647 - 4660[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-03231 RAB Revue Centre de documentation En réserve L003 Exclu du prêt A cognitive pyramid for contextual classification of remote sensing images / E. Binaghi in IEEE Transactions on geoscience and remote sensing, vol 41 n° 12 (December 2003)
[article]
Titre : A cognitive pyramid for contextual classification of remote sensing images Type de document : Article/Communication Auteurs : E. Binaghi, Auteur ; I. Gallo, Auteur ; M. Pepe, Auteur Année de publication : 2003 Article en page(s) : pp 2906 - 2922 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification contextuelle
[Termes IGN] classification dirigée
[Termes IGN] classification par réseau neuronal
[Termes IGN] extraction automatique
[Termes IGN] image aérienne
[Termes IGN] image panchromatique
[Termes IGN] image satellite
[Termes IGN] Perceptron multicouche
[Termes IGN] reconnaissance d'objets
[Termes IGN] résolution multipleRésumé : (Auteur) Many cases of remote sensing classification present complicated patterns that cannot he identified on the basis of spectral data alone, but require contextual methods that base class discrimination on the spatial relationships between the individual pixel and local and global configurations of neighboring pixels. However, the use of contextual classification is still limited by critical issues, such as complexity and problem dependency. We propose here a contextual classification strategy for object recognition in remote sensing images in an attempt to solve recognition tasks operatively. The salient characteristics of the strategy are the definition of a multiresolution feature extraction procedure exploiting human perception and the use of soft neural classification based on the multilayer perceptron model. Three experiments were conducted to evaluate the performance of the methodology, one in an easily controlled domain using synthetic images, the other two in real domains involving builtup pattern recognition in panchromatic aerial photographs and high-resolution satellite images. Numéro de notice : A2003-385 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2003.815409 En ligne : https://doi.org/10.1109/TGRS.2003.815409 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26465
in IEEE Transactions on geoscience and remote sensing > vol 41 n° 12 (December 2003) . - pp 2906 - 2922[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-03121 RAB Revue Centre de documentation En réserve L003 Disponible Segmentation of remotely sensed images using wavelet and their evaluation in soft computing framework / M. Acharyya in IEEE Transactions on geoscience and remote sensing, vol 41 n° 12 (December 2003)
[article]
Titre : Segmentation of remotely sensed images using wavelet and their evaluation in soft computing framework Type de document : Article/Communication Auteurs : M. Acharyya, Auteur ; M.K. Kundu, Auteur ; K., De Rajat, Auteur Année de publication : 2003 Article en page(s) : pp 2900 - 2905 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] image IRS
[Termes IGN] image SPOT
[Termes IGN] intelligence artificielle
[Termes IGN] ondelette
[Termes IGN] recouvrement d'images
[Termes IGN] segmentation d'image
[Termes IGN] télédétection spatialeRésumé : (Auteur) The present paper describes a feature extraction method based on M-band wavelet packet frames for segmenting remotely sensed images. These wavelet features are then evaluated and selected using an efficient neurofuzzy algorithm. Both the feature extraction and neurofuzzy feature evaluation methods are unsupervised, and they do not require the knowledge of the number and distribution of classes corresponding to various land covers in remotely sensed images. The effectiveness of the methodology is demonstrated on two four-band Indian Remote Sensing 1A satellite (IRS-1A) images containing five to six overlapping classes and a three-band SPOT image containing seven overlapping classes. Numéro de notice : A2003-384 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2003.815398 En ligne : https://doi.org/10.1109/TGRS.2003.815398 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26464
in IEEE Transactions on geoscience and remote sensing > vol 41 n° 12 (December 2003) . - pp 2900 - 2905[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-03121 RAB Revue Centre de documentation En réserve L003 Disponible High spatial resolution spectral mixture analysis of urban reflectance / C. Small in Remote sensing of environment, vol 88 n° 1 (30/11/2003)
[article]
Titre : High spatial resolution spectral mixture analysis of urban reflectance Type de document : Article/Communication Auteurs : C. Small, Auteur Année de publication : 2003 Article en page(s) : pp 170 - 186 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] albedo
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] image à résolution métrique
[Termes IGN] image Ikonos
[Termes IGN] milieu urbain
[Termes IGN] radiance
[Termes IGN] réflectanceRésumé : (Auteur) This study uses IKONOS imagery to quantify the combined spatial and spectral charactenistics of urban reflectance in 14 urban areas worldwide. IKONOS 1-m panchromatic imagery provides a detailed measure of spatial variations in albedo while IKONOS 4-m multispectral imagery allows the relative contributions of different matenials to the spectrally heterogeneous radiance field to be determined and their abundance to be mapped. Spatial autocorrelation analyses indicate that the characteristic scale of urban reflectance is consistently between 10 and 20 m for the cities in this study. Spectral mixture analysis quantifies the relative contributions of the dominant spectral endmembers to the overall reflectance of the urban mosaic. Spectral mixing spaces defined by the two low-order principal components account for 96% to 990% of image variance and have a consistent triangular structure spanned by high albedo, low albedo and vegetation endmembers. Spectral mixing among these endmembers is predominantly linear although some nonlinear mixing is observed along the gray axis spanning the high and low albedo endmembers. Inversion of a constrained three-component linear mixing model produces stable, consistent estimates of endmember abundance. RMS errors based on the misfit between observed radiance vectors and modeled radiance vectors (derived from fraction estimates and image endmembers) are generally less than 3% of the mean of the observed radiance. Agreement between observed radiance and fraction estimates does not guarantee the accuracy of the areal fraction estimates, but it does indicate that the three-component linear model provides a consistent and widely applicable physical characterization of urban reflectance. Field validated fraction estimates have applications in urban vegetation monitoring and pervious surface mapping. Numéro de notice : A2003-334 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2003.04.008 En ligne : https://doi.org/10.1016/j.rse.2003.04.008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22629
in Remote sensing of environment > vol 88 n° 1 (30/11/2003) . - pp 170 - 186[article]Mapping forest degradation in the Eastern Amazon SPOT 4 through spectral mixture models / Cristiano B. Souza in Remote sensing of environment, vol 87 n° 4 (15/11/2003)
[article]
Titre : Mapping forest degradation in the Eastern Amazon SPOT 4 through spectral mixture models Type de document : Article/Communication Auteurs : Cristiano B. Souza, Auteur ; L. Firestone, Auteur ; L. Moreira Silva, Auteur ; D. Roberts, Auteur Année de publication : 2003 Article en page(s) : pp 494 - 506 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] analyse visuelle
[Termes IGN] cartographie écologique
[Termes IGN] classification ascendante hiérarchique
[Termes IGN] déboisement
[Termes IGN] image Ikonos
[Termes IGN] image multibande
[Termes IGN] image SPOT
[Termes IGN] statistique mathématiqueRésumé : (Auteur) In this paper, we present a methodology to map classes of degraded forest in the Eastern Amazon. Forest degradation field data, available in the literature, and 1-m resolution IKONOS image were linked with fraction images (vegetation, nonphotosynthetic vegetation (NPV), soil and shade) derived from spectral mixture models applied to a Satellite Pour l'Observation de la Terre (SPOT) 4 multispectral image. The forest degradation map was produced in two steps. First, we investigated the relationship between ground (i.e., field and IKONOS data) and satellite scales by analyzing statistics and performing visual analyses of the field classes in terms of fraction values. This procedure allowed us to define four classes of forest at the SPOT 4 image scale, which included: intact forest; logged forest (recent and older logged forests in the field); degraded forest (heavily burned, heavily logged and burned forests in the field) ; and regeneration (old heavily logged and old heavily burned forest in the field). Next, we used a decision tree classifier (DTQ to define a set of rules to separate the forest classes using the fraction images. We classified 35% of the forest area (2097.3 km2 ) as intact forest. Logged forest accounted for 56% of the forest area and 9% of the forest area was classified as degraded forest. The resultant forest degradation map showed good agreement (86% overall accuracy) with areas of degraded forest visually interpreted from two IKONOS images. In addition, high correlation (R2 = 0.97) was observed between the total live aboveground biomass of degraded forest classes (defined at the field scale) and the NPV fraction image. The NPV fraction also improved our ability to mapping of old selectively logged forests. Numéro de notice : A2003-338 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2002.08.002 En ligne : https://doi.org/10.1016/j.rse.2002.08.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22633
in Remote sensing of environment > vol 87 n° 4 (15/11/2003) . - pp 494 - 506[article]A credit assignment approach to fusing classifiers of multiseason hyperspectral imagery / C. Bachmann in IEEE Transactions on geoscience and remote sensing, vol 41 n° 11 (November 2003)PermalinkA Markov random field approach to spatio-temporal contextual image classification / F. Melgani in IEEE Transactions on geoscience and remote sensing, vol 41 n° 11 (November 2003)PermalinkA combined fuzzy pixel-based and object-based approach for classification of high-resolution multispectral data over urban areas / A.K. Shackelford in IEEE Transactions on geoscience and remote sensing, vol 41 n° 10 (October 2003)PermalinkIncreasing the spatial resolution of agricultural land cover maps using a Hopfield neural network / A.J. Tatem in International journal of geographical information science IJGIS, vol 17 n° 7 (october 2003)PermalinkAutonomous space resection using point- and line-based representation of free-form control linear features / A. Habib in Photogrammetric record, vol 18 n° 103 (September - November 2003)PermalinkComparing ARTMAP neural network with the maximum-likelihood classifier for detecting urban change / K.C. Seto in Photogrammetric Engineering & Remote Sensing, PERS, vol 69 n° 9 (September 2003)PermalinkA hierarchical fuzzy classification approach for high-resolution multispectral data over urban areas / A.K. Shackelford in IEEE Transactions on geoscience and remote sensing, vol 41 n° 9 (September 2003)PermalinkImproving the performance of classifiers in high-dimensional remote sensing applications: an adaptive resampling strategy for error-prone exemplars / C. Bachmann in IEEE Transactions on geoscience and remote sensing, vol 41 n° 9 (September 2003)PermalinkMeasuring the physical composition of urban morphology using multiple endmember spectral mixture models / T. Rashed in Photogrammetric Engineering & Remote Sensing, PERS, vol 69 n° 9 (September 2003)PermalinkSpatial metrics and image texture for mapping urban land use / Martin Herold in Photogrammetric Engineering & Remote Sensing, PERS, vol 69 n° 9 (September 2003)PermalinkImpact of topographic normalization on land-cover classification accuracy / S.R. Hale in Photogrammetric Engineering & Remote Sensing, PERS, vol 69 n° 7 (July 2003)PermalinkEvaluation of airborne video data for land-cover classification accuracy assessment / I.T. Grierson in Geocarto international, vol 18 n° 2 (June - August 2003)PermalinkFusion of spectral and shape features for identification of urban surface cover types using reflective and thermal hyperspectral data / Karl Segl in ISPRS Journal of photogrammetry and remote sensing, vol 58 n° 1-2 (June - December 2003)PermalinkProcessing Hyperion and ALI for forest classification / D.G. Goodenough in IEEE Transactions on geoscience and remote sensing, vol 41 n° 6 (June 2003)PermalinkAssessment of different topographic corrections in Landsat-TM data for mapping vegetation type (2003) / D. Riano in IEEE Transactions on geoscience and remote sensing, vol 41 n° 5 (May 2003)PermalinkComparison of gray-level reduction and different texture spectrum encoding methods for land-use classification using a panchromatic Ikonos image / B. Xu in Photogrammetric Engineering & Remote Sensing, PERS, vol 69 n° 5 (May 2003)PermalinkHyperspectral texture recognition using a multiscale opponent representation / M. Shi in IEEE Transactions on geoscience and remote sensing, vol 41 n° 5 (May 2003)PermalinkImage calibration to like-values in mapping shallow water quality from multitemporal data / M.A.. Islam in Photogrammetric Engineering & Remote Sensing, PERS, vol 69 n° 5 (May 2003)PermalinkMulti-band wavelet for using Spot panchromatic and multispectral images / Wei Shi in Photogrammetric Engineering & Remote Sensing, PERS, vol 69 n° 5 (May 2003)PermalinkQuantitative assessment of a haze suppression methodology for satellite imagery: effect on land cover classification performance / Y. Zhang in IEEE Transactions on geoscience and remote sensing, vol 41 n° 5 (May 2003)Permalink