Centre dedocumentation
scientifique

Indoor positioning using PnP problem on mobile phone images / Hana Kubickova in ISPRS International journal of geo-information, vol 9 n° 6 (June 2020)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 6 (June 2020) . - 19 p. Titre : Indoor positioning using PnP problem on mobile phone images Type de document : Article/Communication Auteurs : Hana Kubickova, Auteur ; Karel Jedlička, Auteur ; Radek Fiala, Auteur ; Daniel Beran, Auteur Année de publication : 2020 Article en page(s) : 19 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] appariement d'images [Termes descripteurs IGN] base de données d'images [Termes descripteurs IGN] décomposition d'image [Termes descripteurs IGN] extraction de traits caractéristiques [Termes descripteurs IGN] géométrie épipolaire [Termes descripteurs IGN] GNSS-INS [Termes descripteurs IGN] point d'appui [Termes descripteurs IGN] positionnement en intérieur [Termes descripteurs IGN] recherche d'image basée sur le contenu [Termes descripteurs IGN] SIFT (algorithme) [Termes descripteurs IGN] téléphone intelligent [Termes descripteurs IGN] vision par ordinateur Résumé : (auteur) As people grow accustomed to effortless outdoor navigation, there is a rising demand for similar possibilities indoors as well. Unfortunately, indoor localization, being one of the requirements for navigation, continues to be a problem without a clear solution. In this article, we are proposing a method for an indoor positioning system using a single image. This is made possible using a small preprocessed database of images with known control points as the only preprocessing needed. Using feature detection with the SIFT (Scale Invariant Feature Transform) algorithm, we can look through the database and find an image that is the most similar to the image taken by a user. Such a pair of images is then used to find coordinates of a database of images using the PnP problem. Furthermore, projection and essential matrices are determined to calculate the user image localization—determining the position of the user in the indoor environment. The benefits of this approach lie in the single image being the only input from a user and the lack of requirements for new onsite infrastructure. Thus, our approach enables a more straightforward realization for building management. Numéro de notice : A2020-309 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9060368 date de publication en ligne : 02/06/2020 En ligne : https://doi.org/10.3390/ijgi9060368 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95156 [article]

Contextual filtering methods based on the subbands and subspaces decomposition of complex SAR interferograms / Saoussen Belhadj-Aissa in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol 12 n° 12 (December 2019)  

Public [article]  inIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing > vol 12 n° 12 (December 2019) . - pp 5321 - 5333 Titre : Contextual filtering methods based on the subbands and subspaces decomposition of complex SAR interferograms Type de document : Article/Communication Auteurs : Saoussen Belhadj-Aissa, Auteur ; Faiza Hocine, Auteur ; Bénédicte Fruneau , Auteur ; Mohamed Salah Boughacha, Auteur ; Karima Hadj-Rabah, Auteur ; Aichouche Belhadj-Aissa, Auteur Année de publication : 2019 Projets : 2-Pas d'info accessible - article non ouvert / Article en page(s) : pp 5321 - 5333 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] bruit (théorie du signal) [Termes descripteurs IGN] décomposition d'image [Termes descripteurs IGN] filtrage numérique d'image [Termes descripteurs IGN] image radar moirée [Termes descripteurs IGN] prise en compte du contexte Résumé : (Auteur) Different forms of phase noise in SAR interferograms hamper the accuracy and reliability of interferometric results (InSAR and DInSAR) for the reconstruction of altimetric information and its variations. Geometric and temporal decorrelations, changes in the properties of observed surfaces and delays introduced by the atmospheric layers are the main sources of interferometric noise. In order to reduce their effects and thus increase the robustness of the phase unwrapping algorithms, filtering methods are applied at different levels of the InSAR and DInSAR processes. In this article, we propose an interferometric filtering process that combines wavelet decomposition into subbands and nonlinear weighting filter called spectral contextual filter (SCF). SCF is based on the Goldstein algorithm, whose nonlinear filter coefficients are calculated, for each element of window according to the filter's punctual parameter. This parameter is determined by estimating the adaptive coherent pseudocorrelation of overlapping blocks of the interferometric phase which combines coherence and pseudocorrelation that are both weighted by the coefficient of variation of each block. In order to show the efficiency and robustness of this process, we compared it with the subspaces decomposition filtering process that we implemented. An assessment scheme was led on the basis of a compromise between residues reduction and fringe boundaries conservation. This assessment was carried relative to the global and local parameters. The tests were conducted on complex interferograms acquired on regions with high topographical variations. Numéro de notice : A2019-273 Affiliation des auteurs : LaSTIG+Ext (2020- ) Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/JSTARS.2019.2957466 date de publication en ligne : 23/12/2019 En ligne : https://doi.org/10.1109/JSTARS.2019.2957466 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95356 [article]

Critical analysis of model-based incoherent polarimetric decomposition methods and investigation of deorientation effect / Pooja Mishra in IEEE Transactions on geoscience and remote sensing, vol 55 n° 9 (September 2017)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 55 n° 9 (September 2017) . - pp 4868 - 4877 Titre : Critical analysis of model-based incoherent polarimetric decomposition methods and investigation of deorientation effect Type de document : Article/Communication Auteurs : Pooja Mishra, Auteur ; Akanksha Garg, Auteur ; Dharmendra Singh, Auteur Année de publication : 2017 Article en page(s) : pp 4868 - 4877 Note générale : Bibliothèque Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] décomposition d'image [Termes descripteurs IGN] diffusion du rayonnement [Termes descripteurs IGN] données polarimétriques [Termes descripteurs IGN] image ALOS [Termes descripteurs IGN] image ALOS-PALSAR [Termes descripteurs IGN] occupation du sol [Termes descripteurs IGN] polarimétrie radar [Termes descripteurs IGN] valeur propre [Termes descripteurs IGN] végétation [Termes descripteurs IGN] zone urbaine Résumé : (Auteur) This paper critically analyzes several incoherent model-based decomposition methods for assessing the effect of deorientation in characterization of various land covers. It has been found that even after performing decomposition, ambiguity still occurs in scattering response from various land covers, such as urban and vegetation. Researchers introduced the concept of deorientation to remove this ambiguity. Therefore, in this paper, a critical analysis has been carried out using seven different three- and four-component decomposition methods with and without deorientation and two Eigen decomposition-based methods to investigate the scattering response on various land covers, such as urban, vegetation, bare soil, and water. The comprehensive evaluation of decomposition and deorientation effect has been performed by both visual and quantitative analyses. Two types of quantitative analysis have been performed; first, by observing percentage of scattering power and second, by analyzing the variation in the number of pixels in different land covers for each scattering contribution. The analysis shows that deorientation increases not only the power but also the number of pixels for surface and double bounce scattering. The number of pixels representing volume scattering remain almost the same for all the methods with or without deorientation, whereas volume scattering power reduces after deorientation. Eigen decomposition-based methods are observed to solve the problem of overestimation of volume scattering power. Numéro de notice : A2017-657 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2017.2652060 En ligne : http://dx.doi.org/10.1109/TGRS.2017.2652060 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=87067 [article]

Parallax-tolerant aerial image georegistration and efficient camera pose refinement—without piecewise homographies / Hadi AliAkbarpour in IEEE Transactions on geoscience and remote sensing, vol 55 n° 8 (August 2017)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 55 n° 8 (August 2017) . - pp 4618 - 4637 Titre : Parallax-tolerant aerial image georegistration and efficient camera pose refinement—without piecewise homographies Type de document : Article/Communication Auteurs : Hadi AliAkbarpour, Auteur ; Kannappan Palaniappan, Auteur ; Guna Seetharaman, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 4618 - 4637 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes descripteurs IGN] bruit (théorie du signal) [Termes descripteurs IGN] chambre de prise de vue numérique [Termes descripteurs IGN] compensation par faisceaux [Termes descripteurs IGN] décomposition d'image [Termes descripteurs IGN] géoréférencement [Termes descripteurs IGN] image aérienne [Termes descripteurs IGN] métadonnées [Termes descripteurs IGN] orthorectification [Termes descripteurs IGN] reconstruction 3D [Termes descripteurs IGN] structure-from-motion Résumé : (Auteur) We describe a fast and efficient camera pose refinement and Structure from Motion (SfM) method for sequential aerial imagery with applications to georegistration and 3-D reconstruction. Inputs to the system are 2-D images combined with initial noisy camera metadata measurements, available from on-board sensors (e.g., camera, global positioning system, and inertial measurement unit). Georegistration is required to stabilize the ground-plane motion to separate camera-induced motion from object motion to support vehicle tracking in aerial imagery. In the proposed approach, we recover accurate camera pose and (sparse) 3-D structure using bundle adjustment for sequential imagery (BA4S) and then stabilize the video from the moving platform by analytically solving for the image-plane-to-ground-plane homography transformation. Using this approach, we avoid relying upon image-to-image registration, which requires estimating feature correspondences (i.e., matching) followed by warping between images (in a 2-D space) that is an error prone process for complex scenes with parallax, appearance, and illumination changes. Both our SfM (BA4S) and our analytical ground-plane georegistration method avoid the use of iterative consensus combinatorial methods like RANdom SAmple Consensus which is a core part of many published approaches. BA4S is very efficient for long sequential imagery and is more than 130 times faster than VisualSfM, 35 times faster than MavMap, and about 274 times faster than Pix4D. Various experimental results demonstrate the efficiency and robustness of the proposed pipeline for the refinement of camera parameters in sequential aerial imagery and georegistration. Numéro de notice : A2017-501 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2017.2695172 En ligne : http://dx.doi.org/10.1109/TGRS.2017.2695172 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86444 [article]

Superpixel-based intrinsic image decomposition of hyperspectral images / Xudong Jin in IEEE Transactions on geoscience and remote sensing, vol 55 n° 8 (August 2017)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 55 n° 8 (August 2017) . - pp 4285 - 4295 Titre : Superpixel-based intrinsic image decomposition of hyperspectral images Type de document : Article/Communication Auteurs : Xudong Jin, Auteur ; Yanfeng Gu, Auteur Année de publication : 2017 Article en page(s) : pp 4285 - 4295 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] classification pixellaire [Termes descripteurs IGN] décomposition d'image [Termes descripteurs IGN] décomposition du pixel [Termes descripteurs IGN] image hyperspectrale [Termes descripteurs IGN] matrice [Termes descripteurs IGN] méthode de réduction d'énergie Résumé : (Auteur) In this paper, we propose a novel superpixel-based intrinsic image decomposition (SIID) framework for hyperspectral images. Intrinsic images are usually referred to the separation of shading and reflectance components from an input image. Considering the high dimensionality of hyperspectral images, we further decompose the shading component into the product of environment illumination and surface orientation changes, thus modeling the problem more properly. The proposed method consists of the following steps. First, we build two superpixel segmentation maps of different scales, i.e., a finer one that is oversegmented and a coarser one that is undersegmented. Based on the observation that the finer superpixel map achieves a higher segmentation accuracy, whereas the coarser superpixel map tends to reserve the objectness of the original image, we model the SIID decomposition problem in a matrix form based on the finer superpixel map and define a constraint matrix by integrating the information in the coarser superpixel map. The constraint matrix is introduced as a secondary constraint in order to make the ill-posed IID problem solvable. Finally, we transform the original decomposition problem into minimizing the Frobenius norm of the proposed matrix energy function and iteratively derive the solution. Our experimental results demonstrate that the proposed method is able to achieve a performance outperforming the state-of-the-art while making a great improvement in efficiency. Numéro de notice : A2017-493 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2017.2690445 En ligne : http://dx.doi.org/10.1109/TGRS.2017.2690445 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86423 [article]

Refining geometry from depth sensors using IR shading images / Gyeongmin Choe in International journal of computer vision, vol 122 n° 1 (March 2017)  

Permalink

Fast three-dimensional empirical mode decomposition of hyperspectral images for class-oriented multitask learning / Zhi He in IEEE Transactions on geoscience and remote sensing, vol 54 n° 11 (November 2016)  

Permalink

Object-based morphological profiles for classification of remote sensing imagery / Christian Geiss in IEEE Transactions on geoscience and remote sensing, vol 54 n° 10 (October 2016)  

Permalink

Regression wavelet analysis for lossless coding of remote-sensing data / Naoufal Amrani in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)  

Permalink

Soil moisture retrieval in agricultural fields using adaptive model-based polarimetric decomposition of SAR data / Lian He in IEEE Transactions on geoscience and remote sensing, vol 54 n° 8 (August 2016)  

Permalink

Multiple morphological component analysis based decomposition for remote sensing image classification / Xiang Xu in IEEE Transactions on geoscience and remote sensing, vol 54 n° 5 (May 2016)  

Permalink

Compressive sensing for multibaseline polarimetric SAR tomography of forested areas / Xinwu Li in IEEE Transactions on geoscience and remote sensing, vol 54 n° 1 (January 2016)  

Permalink

Linear models for airborne-laser-scanning-based operational forest inventory with small field sample size and highly correlated LiDAR data / Virpi Junttila in IEEE Transactions on geoscience and remote sensing, vol 53 n° 10 (October 2015)  

Permalink

Hyperspectral and multispectral image fusion based on a sparse representation / Qi Wei in IEEE Transactions on geoscience and remote sensing, vol 53 n° 7 (July 2015)

Permalink

MTF-adjusted pansharpening approach based on coupled multiresolution decompositions / Abdelaziz Kallel in IEEE Transactions on geoscience and remote sensing, vol 53 n° 6 (June 2015)  

Permalink