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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 A spectral and spatial source separation of multispectral images / M.A. Loghmari in IEEE Transactions on geoscience and remote sensing, vol 44 n° 12 (December 2006)
[article]
Titre : A spectral and spatial source separation of multispectral images Type de document : Article/Communication Auteurs : M.A. Loghmari, Auteur ; Mohamed Saber Naceur, Auteur ; Mohamed-Rached Boussema, Auteur Année de publication : 2006 Article en page(s) : pp 3659 - 3673 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification bayesienne
[Termes IGN] données multisources
[Termes IGN] hétérogénéité
[Termes IGN] image multibande
[Termes IGN] occupation du sol
[Termes IGN] segmentation d'image
[Termes IGN] séparabilité
[Termes IGN] signature spectraleRésumé : (Auteur) This paper deals with the problem of blind source separation of remote sensing data based on a Bayesian estimation framework. We consider the case of multispectral images in which we have observed images of the same zone through different spectral bands. The land cover types existing in the scanned zone constitute the sources to separate. Associating each source to a specific significant theme remains the real challenge in the source-separation method applied to satellite images. In fact, multispectral images consist of multiple channels, each channel containing data acquired from different bands within the frequency spectrum. Since most objects emit or reflect energy over a large spectral bandwidth, there usually exists a significant correlation between channels. This constitutes the first difficulty for sources identification. The second difficulty lies in the heterogeneity of most of the geological and vegetative ground surfaces. In this case, the geometrical projection of a single detector element at the Earth's surface, which is sometimes called the instantaneous field of view, is formed from a mixture of spectral signatures. In such circumstances, the needed information is either not available or not reliable. In this paper, the goal is to establish a new approach based on a two-level source separation (TLSS), which consists of a spectral separation along the different used bands and a spatial separation along neighboring pixels of each image band. The spectral separation has been used prior to the Bayesian approach, and it is based on a second-order statistics approach that exploits the correlation through different spectral bands of the multispectral sensor. The given images are represented according to independent axes that provide more effective representation of the information within the observation images. The spectral separation consists of identifying the sources without resorting to any a priori information, hence the term blind. The obtained source-separation represent the starting point for the Bayesian approach, which is known for its weakness in front of initial conditions. To identify a significant theme for each source, we have to spatially separate each image based on a Bayesian source-separation framework. The proposed approach has the added advantages of the blind source method as well as the Bayesian method. It should give segmented images related to each theme covering the scanned zone, which are the TLSS results of the observation images. Copyright IEEE Numéro de notice : A2006-559 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2006.882261 En ligne : https://doi.org/10.1109/TGRS.2006.882261 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28282
in IEEE Transactions on geoscience and remote sensing > vol 44 n° 12 (December 2006) . - pp 3659 - 3673[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-06121 RAB Revue Centre de documentation En réserve L003 Disponible A review of multi-channel indices of class separability / I.L. Thomas in International Journal of Remote Sensing IJRS, vol 8 n° 3 (March 1987)
[article]
Titre : A review of multi-channel indices of class separability Type de document : Article/Communication Auteurs : I.L. Thomas, Auteur ; N.P. Ching, Auteur ; V.M. Benning, Auteur ; J.A. D' Aguanno, Auteur Année de publication : 1987 Article en page(s) : pp 331 - 350 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse de données
[Termes IGN] analyse multibande
[Termes IGN] classification
[Termes IGN] couleur (variable spectrale)
[Termes IGN] séparabilitéNuméro de notice : A1987-119 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431168708948645 En ligne : https://doi.org/10.1080/01431168708948645 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=24215
in International Journal of Remote Sensing IJRS > vol 8 n° 3 (March 1987) . - pp 331 - 350[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 080-87031 RAB Revue Centre de documentation En réserve L003 Disponible Urban land use separability as a function of radar polarization / F.M. Henderson in International Journal of Remote Sensing IJRS, vol 8 n° 3 (March 1987)
[article]
Titre : Urban land use separability as a function of radar polarization Type de document : Article/Communication Auteurs : F.M. Henderson, Auteur ; K.A. Mogilski, Auteur Année de publication : 1987 Article en page(s) : pp 441 - 448 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] image radar
[Termes IGN] occupation du sol
[Termes IGN] polarisation
[Termes IGN] radar à antenne synthétique
[Termes IGN] séparabilité
[Termes IGN] utilisation du sol
[Termes IGN] zone urbaineNuméro de notice : A1987-125 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431168708948652 En ligne : https://doi.org/10.1080/01431168708948652 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=24221
in International Journal of Remote Sensing IJRS > vol 8 n° 3 (March 1987) . - pp 441 - 448[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 080-87031 RAB Revue Centre de documentation En réserve L003 Disponible