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An approach to extracting digital elevation model for undulating and hilly terrain using de-noised stereo images of Cartosat-1 sensor / Litesh Bopche in Applied geomatics, vol 14 n° 1 (March 2022)  

Public [article]  inApplied geomatics > vol 14 n° 1 (March 2022) . - pp 39 - 55 Titre : An approach to extracting digital elevation model for undulating and hilly terrain using de-noised stereo images of Cartosat-1 sensor Type de document : Article/Communication Auteurs : Litesh Bopche, Auteur ; Priti P. Rege, Auteur Année de publication : 2022 Article en page(s) : pp 39 - 55 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] filtrage du bruit [Termes IGN] image ALOS [Termes IGN] image Cartosat-1 [Termes IGN] Inde [Termes IGN] MNS ASTER [Termes IGN] MNS SRTM [Termes IGN] modèle numérique de surface [Termes IGN] modèle par fonctions rationnelles [Termes IGN] modèle stéréoscopique [Termes IGN] points homologues Résumé : (auteur) A digital elevation model (DEM) is established as an essential geospatial dataset requisite for many topographical and environmental applications. The freely available DEMs have low spatial resolution (SR ≥ 30 m) and comprise considerable vertical errors. The vertical errors are worsened in the undulating and hilly or rugged terrain regions. In this research, we introduced a study to investigate the effect of the noise reduction filters on the accuracy and quality of the DEMs for undulating and hilly terrain regions. The main objectives are to extract a high-quality DEM without collecting physical data like ground control points. DEM generation using de-noised stereo images is carried out using Rational Polynomial Coefficients of Cartosat-1 sensor and Automated Tie Point (ATP) selection. The ATP selection and distribution on the stereo images play a significant role in the DEM accuracy. The present paper also provides information about the optimum number of ATPs used for different topographic conditions. The altitude value of extracted DEM through de-noised stereo images and freely accessible DEMs is compared with reference to the ground truth value of the study region. The 3-D surface profile map of the DEM is used for visual interpretation. Numéro de notice : A2022-216 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s12518-021-00412-0 Date de publication en ligne : 26/11/2021 En ligne : https://doi.org/10.1007/s12518-021-00412-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100086 [article]

A pipeline for automated processing of Corona KH-4 (1962-1972) stereo imagery / Sajid Ghuffar (2022)  

Public contenu dans ArXiv / Université Cornell (Etats-Unis) (1991)   Titre : A pipeline for automated processing of Corona KH-4 (1962-1972) stereo imagery Type de document : Article/Communication Auteurs : Sajid Ghuffar, Auteur ; Tobias Bolch, Auteur ; Ewelina Rupnik , Auteur ; Atanu Bhattacharya, Auteur Editeur : Ithaca [New York - Etats-Unis] : ArXiv - Université Cornell Année de publication : 2022 Projets : 1-Pas de projet / Importance : pp 1 - 24 Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] appariement d'images [Termes IGN] apprentissage profond [Termes IGN] chaîne de traitement [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] compensation par faisceaux [Termes IGN] géométrie de l'image [Termes IGN] géométrie épipolaire [Termes IGN] glacier [Termes IGN] Himalaya [Termes IGN] image Corona [Termes IGN] image panoramique [Termes IGN] MNS SRTM [Termes IGN] modèle numérique de surface [Termes IGN] modèle stéréoscopique [Termes IGN] point d'appui Résumé : (auteur) The Corona KH-4 reconnaissance satellite missions from 1962-1972 acquired panoramic stereo imagery with high spatial resolution of 1.8-7.5 m. The potential of 800,000+ declassified Corona images has not been leveraged due to the complexities arising from handling of panoramic imaging geometry, film distortions and limited availability of the metadata required for georeferencing of the Corona imagery. This paper presents Corona Stereo Pipeline (CoSP): A pipeline for processing of Corona KH-4 stereo panoramic imagery. CoSP utlizes a deep learning based feature matcher SuperGlue to automatically match features point between Corona KH-4 images and recent satellite imagery to generate Ground Control Points (GCPs). To model the imaging geometry and the scanning motion of the panoramic KH-4 cameras, a rigorous camera model consisting of modified collinearity equations with time dependent exterior orientation parameters is employed. The results show that using the entire frame of the Corona image, bundle adjustment using well-distributed GCPs results in an average standard deviation (SD) of less than 2 pixels. We evaluate fiducial marks on the Corona films and show that pre-processing the Corona images to compensate for film bending improves the accuracy. We further assess a polynomial epipolar resampling method for rectification of Corona stereo images. The distortion pattern of image residuals of GCPs and y-parallax in epipolar resampled images suggest that film distortions due to long term storage as likely cause of systematic deviations. Compared to the SRTM DEM, the Corona DEM computed using CoSP achieved a Normalized Median Absolute Deviation (NMAD) of elevation differences of ? 4m over an area of approx. 4000km2. We show that the proposed pipeline can be applied to sequence of complex scenes involving high relief and glacierized terrain and that the resulting DEMs can be used to compute long term glacier elevation changes over large areas. Numéro de notice : P2022-001 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : IMAGERIE Nature : Article nature-HAL : Préprint DOI : sans Date de publication en ligne : 09/01/2022 En ligne : https://arxiv.org/abs/2201.07756 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99614

Digital building-height preparation from satellite stereo images / P.S. Prakash in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 8 (August 2021)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 87 n° 8 (August 2021) . - pp 557 - 566 Titre : Digital building-height preparation from satellite stereo images Type de document : Article/Communication Auteurs : P.S. Prakash, Auteur ; Bharath H. Aithal, Auteur Année de publication : 2021 Article en page(s) : pp 557 - 566 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] analyse comparative [Termes IGN] hauteur du bâti [Termes IGN] modèle numérique de surface [Termes IGN] modèle numérique de terrain [Termes IGN] modèle stéréoscopique [Termes IGN] objet géographique urbain [Termes IGN] qualité des données Résumé : (Auteur) Buildings are considered prominent objects for understanding the pattern of growth in an urban setting. Remote sensing technology plays a vital role in facilitating data generation pertaining to various urban applications. Digital surface models represent the elevation of the earth surface features, and can be obtained from stereo images, radar, laser scanning, and so on. Photogrammetric techniques applied to optical stereo satellite images are economical and fast ways to generate height information of buildings. In this work, a quantitative and qualitative analysis of digital surface models generated from Cartosat-1 stereo images is compared with openly available data. The study finds that it is possible to acquire about 50 percent of building heights with acceptable error limits. The experimental results indicate that the quality of height information is suitable for applications to assess urban development at a macro scale, but not for individual building-level modeling. Numéro de notice : A2021-669 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.87.8.557 Date de publication en ligne : 01/08/2021 En ligne : https://doi.org/10.14358/PERS.87.8.557 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98785 [article]

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Automated registration of SfM‐MVS multitemporal datasets using terrestrial and oblique aerial images / Luigi Parente in Photogrammetric record, vol 36 n° 173 (March 2021)  

Public [article]  inPhotogrammetric record > vol 36 n° 173 (March 2021) . - pp 12 - 35 Titre : Automated registration of SfM‐MVS multitemporal datasets using terrestrial and oblique aerial images Type de document : Article/Communication Auteurs : Luigi Parente, Auteur ; Jim H. Chandler, Auteur ; Neil Dixon, Auteur Année de publication : 2021 Article en page(s) : pp 12 - 35 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] algorithme ICP [Termes IGN] alignement [Termes IGN] Angleterre [Termes IGN] détection de changement [Termes IGN] données multisources [Termes IGN] données multitemporelles [Termes IGN] géoréférencement direct [Termes IGN] image aérienne oblique [Termes IGN] image captée par drone [Termes IGN] image oblique [Termes IGN] image terrestre [Termes IGN] modèle stéréoscopique [Termes IGN] modélisation 3D [Termes IGN] point d'appui [Termes IGN] semis de points [Termes IGN] SIFT (algorithme) [Termes IGN] structure-from-motion Résumé : (auteur) Accurate alignment of 3D models is critical for valid change‐detection analysis from multitemporal photogrammetric datasets. This paper assesses an automated registration strategy which uses the scale‐invariant feature transform (SIFT) algorithm implemented in modern photogrammetric software. This registration solution, also known as “Time‐SIFT”, was tested at two study sites featuring vertical surfaces, including a sea cliff (~500 m2) and a quarry face (~50 000 m2). Tests demonstrated that the investigated registration strategy can achieve accurate alignments between multitemporal point clouds even when using multisource and multi‐perspective data, captured across widely varying spatial and temporal scales and under a range of weather and illumination conditions. The combination of the Time‐SIFT approach with an ICP algorithm produced moderate improvements in the alignment. Furthermore, the use of an innovative direct georeferencing technique, which used the tracking feature of a robotic total station, allowed for accurate georectification of 3D models. Numéro de notice : A2021-280 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.1111/phor.12346 Date de publication en ligne : 06/01/2021 En ligne : https://doi.org/10.1111/phor.12346 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97377 [article]

Activity recognition in residential spaces with Internet of things devices and thermal imaging / Kshirasagar Naik in Sensors, vol 21 n° 3 (February 2021)  

Public [article]  inSensors > vol 21 n° 3 (February 2021) . - n° 988 Titre : Activity recognition in residential spaces with Internet of things devices and thermal imaging Type de document : Article/Communication Auteurs : Kshirasagar Naik, Auteur ; Tejas Pandit, Auteur ; Nitin Naik, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 988 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] compréhension de l'image [Termes IGN] contrôle par télédétection [Termes IGN] détection d'événement [Termes IGN] espace intérieur [Termes IGN] image RVB [Termes IGN] image thermique [Termes IGN] intelligence artificielle [Termes IGN] internet des objets [Termes IGN] itération [Termes IGN] modèle stéréoscopique [Termes IGN] objet mobile [Termes IGN] reconnaissance automatique [Termes IGN] reconnaissance d'objets [Termes IGN] scène 3D Résumé : (auteur) In this paper, we design algorithms for indoor activity recognition and 3D thermal model generation using thermal images, RGB images, captured from external sensors, and the internet of things setup. Indoor activity recognition deals with two sub-problems: Human activity and household activity recognition. Household activity recognition includes the recognition of electrical appliances and their heat radiation with the help of thermal images. A FLIR ONE PRO camera is used to capture RGB-thermal image pairs for a scene. Duration and pattern of activities are also determined using an iterative algorithm, to explore kitchen safety situations. For more accurate monitoring of hazardous events such as stove gas leakage, a 3D reconstruction approach is proposed to determine the temperature of all points in the 3D space of a scene. The 3D thermal model is obtained using the stereo RGB and thermal images for a particular scene. Accurate results are observed for activity detection, and a significant improvement in the temperature estimation is recorded in the 3D thermal model compared to the 2D thermal image. Results from this research can find applications in home automation, heat automation in smart homes, and energy management in residential spaces. Numéro de notice : A2021-159 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/s21030988 Date de publication en ligne : 02/02/2021 En ligne : https://doi.org/10.3390/s21030988 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97075 [article]

Apport de la photogrammétrie satellite pour la modélisation du manteau neigeux / César Deschamps-Berger (2021)  

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Improving traffic sign recognition results in urban areas by overcoming the impact of scale and rotation / Roholah Yazdan in ISPRS Journal of photogrammetry and remote sensing, vol 171 (January 2021)  

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Operational monitoring of gravitational movements with image time series / Mathilde Desrues (2021)  

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Stereophotogrammetry for 2-D building deformation monitoring using Kalman Filter / J.O. Odumosu in Reports on geodesy and geoinformatics, vol 110 n° 1 (December 2020)  

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Application of 30-meter global digital elevation models for compensating rational polynomial coefficients biases / Amin Alizadeh Naeini in Geocarto international, vol 35 n° 12 ([01/09/2020])  

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Post‐filtering with surface orientation constraints for stereo dense image matching / Xu Huang in Photogrammetric record, vol 35 n° 171 (September 2020)  

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Vehicle detection of multi-source remote sensing data using active fine-tuning network / Xin Wu in ISPRS Journal of photogrammetry and remote sensing, vol 167 (September 2020)  

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Leveraging photogrammetric mesh models for aerial-ground feature point matching toward integrated 3D reconstruction / Qing Zhu in ISPRS Journal of photogrammetry and remote sensing, vol 166 (August 2020)  

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Learning stereo reconstruction with deep neural networks / Stepan Tulyakov (2020)  

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Occlusion probability in operational forest inventory field sampling with ForeStereo / Fernando Montes in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 7 (July 2019)  

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