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A novel automatic structural linear feature-based matching method based on new concepts of mathematically-generated-points and lines / Somayeh Yavari in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 5 (May 2016)
[article]
Titre : A novel automatic structural linear feature-based matching method based on new concepts of mathematically-generated-points and lines Type de document : Article/Communication Auteurs : Somayeh Yavari, Auteur ; Mohammad Javad Valadan Zoej, Auteur ; Mahmod Reza Sahebi, Auteur ; Mehdi Mokhtarzade, Auteur Année de publication : 2016 Article en page(s) : pp 365 - 376 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] accentuation d'image
[Termes IGN] appariement de données localisées
[Termes IGN] appariement de formes
[Termes IGN] espace objet
[Termes IGN] ligne caractéristiqueRésumé : (Auteur) This paper investigates reliable automatic high resolution image to map matching using a novel structural linear feature-based matching (SLIM) method. The main components used by this method are the specific patterns as well as the lines and points generated mathematically. These components are produced by extension and intersection of extracted line-segments. Due to the high numbers of extracted line-segments in both image and object space, the number of possible patterns is very high. In order to decrease the search space, the innovative SLIM method is performed in three main phases. In the first phase, using a new weighting procedure, only optimum numbers of high-qualified well-distributed patterns, which are more likely to have any correspondence in object space, are selected. In the second phase, the aim is to find a pair with maximum numbers of conjugate lines. To do so, all the possible patterns in object space are screened for each selected image pattern using four predefined geometric criteria. Simultaneously, the correspondence of the other crossing lines is also determined in the same manner. In third phase, the pair with maximum numbers of matched-lines is selected among all the results of second phase. Additionally, the final-phase is done to increase the amount of correctly matched-lines. The main contribution of this investigation is automatic and correct matching of linear features with no need to any initial information. Additionally, the end-points of the corresponding lines are not necessarily conjugate points. The results show the high potential of the proposed method in terms of accuracy, reliability, automation, and time reduction even in images with repetitive patterns or a high numbers of outliers. Numéro de notice : A2016-411 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.82.5.365 En ligne : http://dx.doi.org/10.14358/PERS.82.5.365 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81277
in Photogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 5 (May 2016) . - pp 365 - 376[article]A synchronization algorithm for spaceborne/stationary BiSAR imaging based on contrast optimization with direct signal from radar satellite / M. Zhang in IEEE Transactions on geoscience and remote sensing, vol 54 n° 4 (April 2016)
[article]
Titre : A synchronization algorithm for spaceborne/stationary BiSAR imaging based on contrast optimization with direct signal from radar satellite Type de document : Article/Communication Auteurs : M. Zhang, Auteur ; Robert Wang, Auteur ; Y. Deng, Auteur Année de publication : 2016 Article en page(s) : pp 1977 - 1989 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] amélioration du contraste
[Termes IGN] image radar moirée
[Termes IGN] optimisation (mathématiques)
[Termes IGN] radar bistatique
[Termes IGN] synchronisationRésumé : (Auteur) This paper proposes a synchronization algorithm for bistatic synthetic aperture radar (BiSAR) imaging in a spaceborne/stationary configuration. In real bistatic systems, synchronization errors are generally introduced into the received data. Additionally, the lack of precise imaging parameters, such as the position of the transmitter and the accurate sampling time, could affect the imaging quality greatly. Fortunately, the image could be well focused by the proposed algorithm in the case of lack of the accurate position of a transmitter and the sampling time. First, a preprocessing step is employed to remove synchronization errors through matching an echo signal with a direct signal. Then, a modified chirp scaling factor containing an error phase term is constructed, and the accurate position of the transmitter and the sampling time can be acquired by the phase extraction of the direct signal and the searching method based on contrast optimization. After that, the corresponding imaging process can be implemented. Finally, the proposed algorithm is validated by the simulation and experimental results, where TerraSAR-X is used as the illuminator. Numéro de notice : A2016-837 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2493078 En ligne : http://dx.doi.org/10.1109/TGRS.2015.2493078 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82881
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 4 (April 2016) . - pp 1977 - 1989[article]Dense image matching / Martin Kodde in GIM international [en ligne], vol 30 n° 1 (January 2016)
[article]
Titre : Dense image matching Type de document : Article/Communication Auteurs : Martin Kodde, Auteur Année de publication : 2016 Article en page(s) : pp 28 -29 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] accentuation d'image
[Termes IGN] données massives
[Termes IGN] semis de points
[Termes IGN] vision par ordinateurRésumé : (éditeur) Point clouds are increasingly a prime data source for 3D information. For many years, Lidar systems have been the primary way to create point clouds. More recently, advances in the field of computer vision have allowed for the generation of detailed and reliable point clouds from images - not only from traditional aerial photographs but also from uncalibrated photos from consumer-grade cameras. Dense image matching is the powerful technology underpinning this development. Numéro de notice : A2016-015 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79347
in GIM international [en ligne] > vol 30 n° 1 (January 2016) . - pp 28 -29[article]Remote Sensing Observations of Continental Surfaces, ch. 6. Airborne lidar data processing / Clément Mallet (2016)
contenu dans Remote Sensing Observations of Continental Surfaces, vol 1. Optical Remote Sensing of Land Surface / Nicolas Baghdadi (2016)
Titre de série : Remote Sensing Observations of Continental Surfaces, ch. 6 Titre : Airborne lidar data processing Type de document : Chapitre/Contribution Auteurs : Clément Mallet , Auteur ; Nesrine Chehata , Auteur ; Jean-Stéphane Bailly, Auteur Editeur : Londres : ISTE Press Année de publication : 2016 Importance : pp 249 - 298 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse en composantes principales
[Termes IGN] attribut
[Termes IGN] classification
[Termes IGN] déconvolution
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forme d'onde
[Termes IGN] ondelette
[Termes IGN] reconnaissance de formes
[Termes IGN] segmentation
[Termes IGN] semis de points
[Termes IGN] signal laserRésumé : (auteur) This chapter introduces the main data analysis methods associated with topographic and bathymetric airborne LiDAR systems. Data delivered by these sensors can be of two types: the majority of commercial systems deliver three-dimensional (3D) point clouds (systems referred to as multiecho), whereas a limited number directly provides the whole laser signal backscattered by the Earth surface (systems referred to as full-waveform (FW)). Numéro de notice : H2016-009 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Chapître / contribution nature-HAL : ChOuvrScient DOI : 10.1016/B978-1-78548-102-4.50006-5 Date de publication en ligne : 07/10/2016 En ligne : https://doi.org/10.1016/B978-1-78548-102-4.50006-5 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91789 Collaborative sparse regression for hyperspectral unmixing / Marian-Daniel Iordache in IEEE Transactions on geoscience and remote sensing, vol 52 n° 1 tome 1 (January 2014)
[article]
Titre : Collaborative sparse regression for hyperspectral unmixing Type de document : Article/Communication Auteurs : Marian-Daniel Iordache, Auteur ; José Bioucas-Dias, Auteur ; Antonio J. Plaza, Auteur Année de publication : 2014 Article en page(s) : pp 341 - 354 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] accentuation d'image
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] image hyperspectrale
[Termes IGN] régressionRésumé : (Auteur) Sparse unmixing has been recently introduced in hyperspectral imaging as a framework to characterize mixed pixels. It assumes that the observed image signatures can be expressed in the form of linear combinations of a number of pure spectral signatures known in advance (e.g., spectra collected on the ground by a field spectroradiometer). Unmixing then amounts to finding the optimal subset of signatures in a (potentially very large) spectral library that can best model each mixed pixel in the scene. In this paper, we present a refinement of the sparse unmixing methodology recently introduced which exploits the usual very low number of endmembers present in real images, out of a very large library. Specifically, we adopt the collaborative (also called “multitask” or “simultaneous”) sparse regression framework that improves the unmixing results by solving a joint sparse regression problem, where the sparsity is simultaneously imposed to all pixels in the data set. Our experimental results with both synthetic and real hyperspectral data sets show clearly the advantages obtained using the new joint sparse regression strategy, compared with the pixelwise independent approach. Numéro de notice : A2014-038 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2240001 En ligne : https://doi.org/10.1109/TGRS.2013.2240001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32943
in IEEE Transactions on geoscience and remote sensing > vol 52 n° 1 tome 1 (January 2014) . - pp 341 - 354[article]Réservation
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