The main learning outcomes include:
1. Digital representation of images/videos
2. Point-based image transformations
3. Spatial image transformations and spatial image transformations (image filters)
4. Geometric image transformations and affine transformation
5. Colour spaces
6. Techniques for equalizing image histograms and histogram transformations (histogram equalizations and transformstions)
7. Τεχνικές κατάτμησης εικόνων (image segmenation and semantic segmentation)
8. Epipolar geometry and epipolar lines, Creation of an epipolar geometry, fundamental and essential matrix
9. Image alignment
10. Find optical descriptors invariant ti geometric transformations (Harris Corner and SIFT)
11. Outlier detection and removal techniques
12. Simple data clustering techniques
13. Techniques for finding parallax and calculating depth (disparity field estimation and depth)
Upon completion of the course, the student will have advanced knowledge in photogrammetry issues that entail an understanding of the principles and theory of digital photogrammetry and automation
- Teacher: Αναστάσιος Δουλάμης
- Teacher: Μαρία Πατεράκη
ECTS : 5
Language : el
Learning Outcomes : Upon successful completion of the course, the student will have developed the following skills: • Will be able to successfully complete a full photogrammetric project • Will be able to evaluate modern photogrammetric products from all aspects • Produce digital terrain models, orthophotos and other modern digital photogrammetric derivatives • Be able to address photogrammetric programming issues, which will help him/her in solving complex photogrammetric problems and 3D reconstruction problems in the field of work of the Rural and Surveying Engineer.