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Image Interpretation
Last Updated: 2026-02-05 15:34:51
Abstract
Introduction to interactive, semi-automatic and automatic methods for image interpretation and data analysis; methodological aspects of computer-assisted remote sensing, including semantic image classification and segmentation; detection and extraction of individual objects; estimation of physical parameters.
Objective
Understanding the tasks, problems, and applications of image interpretation; basic introduction of computational methods for image-based classification and parameter estimation (clustering, classification, regression), with focus on remote sensing.
Content
Image (and point-cloud) interpretation tasks: semantic classification (e.g. land-cover mapping), physical parameter estimation (e.g. forest biomass); Image coding and features; probabilistic inference, generative and discriminative models; clustering and segmentation; continuous parameter estimation, regression; classification and labeling; deep learning; atmospheric influences in satellite remote sensing;
Resources
Literature
J. A. Richards: Remote Sensing Digital Image Analysis - An Introduction C. Bishop: Pattern Recognition and Machine Learning
General Information
- Language
- English
- Levels
- MSC
- Frequency
- Yearly recurring
Examination
- Type
- session examination
- Mode
- oral 30 minutes
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture with exercise |
Image Interpretation
In Präsenz: 12. Nov, 19. Nov; HIL C71 (IGP Computerlabor); praktische Übung erfordert spezielle Computer-Hardware und Software.
|
|
3 h weekly |