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Distinctive order based self-similarity descriptor for multi-sensor remote sensing image matching / Amin Sedaghat in ISPRS Journal of photogrammetry and remote sensing, vol 108 (October 2015)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 108 (October 2015) . - pp 62 – 71 Titre : Distinctive order based self-similarity descriptor for multi-sensor remote sensing image matching Type de document : Article/Communication Auteurs : Amin Sedaghat, Auteur ; Hamid Ebadi, Auteur Année de publication : 2015 Article en page(s) : pp 62 – 71 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] appariement d'images [Termes IGN] extraction automatique [Termes IGN] image Geoeye [Termes IGN] image IRS [Termes IGN] image Landsat-ETM+ [Termes IGN] image multicapteur [Termes IGN] image Quickbird [Termes IGN] image SPOT 4 [Termes IGN] image SPOT 5 [Termes IGN] image SPOT 6 [Termes IGN] image Terra-ASTER [Termes IGN] image Worldview [Termes IGN] invariant [Termes IGN] SIFT (algorithme) Résumé : (auteur) Robust, well-distributed and accurate feature matching in multi-sensor remote sensing image is a difficult task duo to significant geometric and illumination differences. In this paper, a robust and effective image matching approach is presented for multi-sensor remote sensing images. The proposed approach consists of three main steps. In the first step, UR-SIFT (Uniform robust scale invariant feature transform) algorithm is applied for uniform and dense local feature extraction. In the second step, a novel descriptor namely Distinctive Order Based Self Similarity descriptor, DOBSS descriptor, is computed for each extracted feature. Finally, a cross matching process followed by a consistency check in the projective transformation model is performed for feature correspondence and mismatch elimination. The proposed method was successfully applied for matching various multi-sensor satellite images as: ETM+, SPOT 4, SPOT 5, ASTER, IRS, SPOT 6, QuickBird, GeoEye and Worldview sensors, and the results demonstrate its robustness and capability compared to common image matching techniques such as SIFT, PIIFD, GLOH, LIOP and LSS. Numéro de notice : A2015-852 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.06.003 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.06.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79222 [article]

Accurate affine invariant image matching using oriented least square / Amin Sedaghat in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 9 (September 2015)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 81 n° 9 (September 2015) . - pp 733 - 793 Titre : Accurate affine invariant image matching using oriented least square Type de document : Article/Communication Auteurs : Amin Sedaghat, Auteur ; Hamid Ebadi, Auteur Année de publication : 2015 Article en page(s) : pp 733 - 793 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] appariement automatique [Termes IGN] appariement d'images [Termes IGN] corrélation à l'aide de traits caractéristiques [Termes IGN] corrélation par moindres carrés [Termes IGN] détection de coins Harris [Termes IGN] extraction de traits caractéristiques [Termes IGN] MSER (algorithme) Résumé : (auteur) Image matching is a vital process for many photogrammetric and remote sensing applications such as image registration and aerial triangulation. In this paper, an accurate affine invariant image matching approach is presented. The proposed approach consists of three main steps. In the first step, two affine invariant feature detectors, including MSER and Harris-Affine features are applied for feature extraction. In the second step, initial corresponding features are selected using Euclidean distance between feature descriptors, followed by a consistency check process. Finally to overcome low positional accuracy of the local affine feature, an advanced version of the least square matching (LSM) namely, Oriented Least Square Matching (OLSM) is developed. Wellknown LSM method has been widely accepted as one of the most accurate methods to obtain high reliable corresponding points from a stereo image pair. However, it is sensitive to significant geometric distortion and requires very good initial approximation. In the proposed OLSM method, shape and size of the matching window are appropriately approximated using obtained affine shape information of the initial elliptical feature pairs. The proposed method was successfully applied for matching various synthetic and real close range and satellite images. Results demonstrate its accuracy and capability compared to standard LSM method Numéro de notice : A2015-986 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.81.9.733 En ligne : https://doi.org/10.14358/PERS.81.9.733 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80267 [article]

Very high resolution image matching based on local features and k-means clustering / Amin Sedaghat in Photogrammetric record, vol 30 n° 150 (June - August 2015)  

Public [article]  inPhotogrammetric record > vol 30 n° 150 (June - August 2015) . - pp 166 - 186 Titre : Very high resolution image matching based on local features and k-means clustering Type de document : Article/Communication Auteurs : Amin Sedaghat, Auteur ; Hamid Ebadi, Auteur Année de publication : 2015 Article en page(s) : pp 166 - 186 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] appariement d'images [Termes IGN] distance euclidienne [Termes IGN] extraction de traits caractéristiques [Termes IGN] image à très haute résolution [Termes IGN] partitionnement [Termes IGN] primitive géométrique Résumé : (Auteur) Image matching is a critical process in photogrammetry and remote sensing. Automatic and reliable feature matching using well-distributed points in very high resolution images is a difficult task due to significant relief displacement caused by tall buildings and ground relief. In this paper a robust and efficient image-matching approach is proposed, consisting of two main steps. In the first step, three sets of local features – Harris points, UR-SIFT and MSER – are extracted over the entire image. A SIFT (scale-invariant feature transform) descriptor is then created for each extracted feature, and an initial cross-matching verification is performed using the Euclidean distance between feature descriptors. In the second step, an approach based on k-means clustering is performed to achieve accurate matching without mismatched features, followed by a consistency check using a local affine transformation model for each cluster. The proposed method is successfully applied to matching various aerial and satellite images and the results demonstrate its robustness and capability. Numéro de notice : A2015-366 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/phor.12101 Date de publication en ligne : 29/06/2015 En ligne : https://doi.org/10.1111/phor.12101 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76908 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
106-2015021	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Automatic building extraction using a fuzzy active contour model / Mostafa Kabolizade in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 11 (November 2014)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 80 n° 11 (November 2014) . - pp 1061 - 1068 Titre : Automatic building extraction using a fuzzy active contour model Type de document : Article/Communication Auteurs : Mostafa Kabolizade, Auteur ; Hamid Ebadi, Auteur ; Mehdi Mokhtarzade, Auteur Année de publication : 2014 Article en page(s) : pp 1061 - 1068 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] détection de contours [Termes IGN] détection du bâti [Termes IGN] extraction automatique Résumé : (Auteur) Automatic building extraction is currently an important research topic in the field of photagrammetry. An active contour model is a well-received approach in this field. This paper proposes an improved active contour model that focuses on building extraction from aerial images and lidar data. The main research concern in this paper is the development of energy functions to the optimum use of expert human knowledge in the overall process. Based on this approach, a new fuzzy inference system for evaluating energy functions was developed by modeling the human perception of various effective parameters in the energy functions. (Compared to the existing active contour models, the new algorithm is capable of directing the initial contour to building feature boundaries more quickly and robustly. Accuracy assessment showed that the proposed model is capable of achieving a shape accuracy of 98 percent and a total accuracy of 97 percent in complex urban areas. Numéro de notice : A2014-617 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.80.11.1061 En ligne : https://doi.org/10.14358/PERS.80.11.1061 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74923 [article]

Automatic reconstruction of regular buildings using a shape-based balloon snake model / Diaro Yari in Photogrammetric record, vol 29 n° 146 (June - August 2014)  

Public [article]  inPhotogrammetric record > vol 29 n° 146 (June - August 2014) . - pp 187 - 205 Titre : Automatic reconstruction of regular buildings using a shape-based balloon snake model Type de document : Article/Communication Auteurs : Diaro Yari, Auteur ; Mehdi Mokhtarzade, Auteur ; Hamid Ebadi, Auteur Année de publication : 2014 Article en page(s) : pp 187 - 205 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] détection de contours [Termes IGN] détection du bâti [Termes IGN] image numérique [Termes IGN] modèle géométrique du bâti [Termes IGN] reconstruction 3D du bâti Résumé : (Auteur) Buildings are regarded as the most prominent man-made objects: hence, their automatic extraction from aerial and satellite images has attracted the interest of photogrammetric research communities. In this paper, a balloon snake, a well-known active contour model, was developed for the precise extraction of building boundaries. Traditional active contours are highly sensitive to image data and are problematic when building boundaries are weakened, usually due to occlusions. To improve the efficiency of the traditional balloon snake model, a shape-based balloon snake model was introduced where knowledge about the expected geometrical shape of buildings was modelled and applied to the traditional snake representation. Implementation of the proposed algorithm confirmed its efficiency in the precise extraction of building boundaries. Experimental results and the qualitative and quantitative evaluations demonstrate the potential of the proposed shape-based balloon snake model and its superiority over traditional models. Numéro de notice : A2014-280 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/phor.12060 Date de publication en ligne : 15/06/2014 En ligne : https://doi.org/10.1111/phor.12060 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=33183 [article]