Buch, Englisch, 335 Seiten, Book, Format (B × H): 155 mm x 235 mm, Gewicht: 640 g
Proceedings of Concerted Action MAVIRIC (Machine Vision in Remotely Sensed Image Comprehension)
Buch, Englisch, 335 Seiten, Book, Format (B × H): 155 mm x 235 mm, Gewicht: 640 g
ISBN: 978-3-540-65571-8
Verlag: Springer-Verlag GmbH
Zielgruppe
Professional/practitioner
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Informatik Bildsignalverarbeitung
- Wirtschaftswissenschaften Wirtschaftssektoren & Branchen Fertigungsindustrie Luftfahrtindustrie
- Technische Wissenschaften Sonstige Technologien | Angewandte Technik Signalverarbeitung, Bildverarbeitung, Scanning
- Geowissenschaften Geologie GIS, Geoinformatik
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Grafikprogrammierung
- Technische Wissenschaften Verkehrstechnik | Transportgewerbe Luft- und Raumfahrttechnik, Luftverkehr
- Technische Wissenschaften Sonstige Technologien | Angewandte Technik Angewandte Optik
- Geowissenschaften Geographie | Raumplanung Geodäsie, Kartographie, GIS, Fernerkundung
- Geowissenschaften Geologie Geodäsie, Kartographie, Fernerkundung
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Computer Vision
Weitere Infos & Material
Foreword.- I. Image Processing and Computer Vision Methods for Remote Sensing Data.- Recent Developments in Remote Sensing Technology and the Importance of Computer Vision Analysis Techniques.- Posing Structural Matching in Remote Sensing as an Optimisation Problem.- Detail-Preserving Processing of Remote Sensing Images.- Multi-Channel Remote Sensing Data and Orthogonal Transformations for Change Detection.- Aspects of Multi-Scale Analysis for Managing Spectral and Temporal Coverages of Space-Borne High-Resolution Images.- Structural Inference Using Deformable Models.- Terrain Feature Recognition Through Structural Pattern Recognition, Knowledge-Based Systems, and Geomorphometric Techniques.- II. High Resolution Data.- Environmental Mapping Based on High Resolution Remote Sensing Data.- Potential Role of Very High Resolution Optical Satellite Image Pre-Processing for Product Extraction.- Forestry Applications of High Resolution Imagery.- Image Analysis Techniques for Urban Land Use Classification. The Use of Kernel Based Approaches to Process Very High Resolution Satellite Imagery.- III. Visualisation, 3D and Stereo.- Automated Change Detection in Remotely Sensed Imagery.- A 3-Dimensional Multi-View Based Strategy for Remotely Sensed Image Interpretation.- 3D Exploitation of SAR Images.- Visualizing Remotely Sensed Depth Maps using Voxels.- Three Dimensional Surface Registration of Stereo Images and Models from MR Images.- Exploring Multi-Dimensional Remote Sensing Data with a Virtual Reality System.- IV. Image Interpretation and Classification.- Information Mining in Remote Sensing Image Archives.- Fusion of Spatial and Temporal Information for Agricultural Land Use Identification - Preliminary Study for the VEGETATION Sensor.- Rule-based Identification of Revision Objects in Satellite Images.- Land Cover Mapping from Optical Satellite Images Employing Subpixel Segmentation and Radiometric Calibration.- Semi-Automatic Analysis of High-Resolution Satellite Images.- Density-Based Unsupervised Classification for Remote Sensing.- Classification of Compressed Multispectral Data.- V. Segmentation and Feature Extraction.- Detection of Urban Features Using Morphological Based Segmentation and Very High Resolution Remotely Sensed Data.- Non-Linear Line Detection Filters.- Fuzzy Clustering and Pyramidal Hough Transform for Urban Features Detection in High Resolution SAR Images.- Detecting Nets of Linear Structures in Satellite Images.- Satellite Image Segmentation Through Rotational Invariant Feature Eigenvector Projection.- Supervised Segmentation by Region Merging.