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Auteur Chiman Kwan |
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Titre : Recent advances in image restoration with applications to real world problems Type de document : Monographie Auteurs : Chiman Kwan, Éditeur scientifique Editeur : London [UK] : IntechOpen Année de publication : 2020 ISBN/ISSN/EAN : 978-1-83968-356-5 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] apprentissage non-dirigé
[Termes IGN] données spatiotemporelles
[Termes IGN] extraction de modèle
[Termes IGN] fusion d'images
[Termes IGN] image hyperspectrale
[Termes IGN] modèle numérique de terrain
[Termes IGN] reconstruction 3D
[Termes IGN] restauration d'imageRésumé : (Editeur) In the past few decades, imaging hardware has improved tremendously in terms of resolution, making widespread usage of images in many diverse applications on Earth and planetary missions. However, practical issues associated with image acquisition are still affecting image quality. Some of these issues such as blurring, measurement noise, mosaicing artifacts, low spatial or spectral resolution, etc. can seriously affect the accuracy of the aforementioned applications. This book intends to provide the reader with a glimpse of the latest developments and recent advances in image restoration, which includes image super-resolution, image fusion to enhance spatial, spectral resolution, and temporal resolutions, and the generation of synthetic images using deep learning techniques. Some practical applications are also included. Note de contenu :
1. Introductory Chapter: Recent Advances in Image Restoration
2. Resolution Enhancement of Hyperspectral Data Exploiting Real Multi-Platform Data
3. Application of Deep Learning Approaches for Enhancing Mastcam Images
4. Generative Adversarial Networks for Visible to Infrared Video Conversion
5. Style-Based Unsupervised Learning for Real-World Face Image Super-Resolution
6. Spatiotemporal Fusion in Remote Sensing
7. 3D Reconstruction through Fusion of Cross-View Images
8. Practical Digital Terrain Model Extraction Using Image Inpainting TechniquesNuméro de notice : 26695 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Recueil / ouvrage collectif DOI : 10.5772/intechopen.90607 Date de publication en ligne : 04/11/2020 En ligne : https://doi.org/10.5772/intechopen.90607 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99081