| Recommended semester: 4th -7th semester |
| Scope and form: Lectures and computer exercises. |
Evaluation: Approval of exercises and reports
The report is about a small, individual project. |
| Examination: Pass/fail |
| Previous course: 04351 og 04451 |
| Prerequisites: 02501 / 04250 / C8817. 02409 / 04241 / C0411 |
| No credit points with: C0466, 04351 |
| Participant limitation: Max. 20 |
| Aim: To give a knowledge of advanced statistical methods and models for analysing image data, and give kompetence i applying these techniques in different applications. The course attempts at making the participants recognize that the use of appropriate statistical models can extract useful knowledge from image data - knowledge that is not directly accessible. |
| Contents: Markov random fields, conditional and simultaneous distributions, simulation and estimation, Bayesian image analysis, orthogonal transformations of multispectral images, texture modelling, geostatistical models, kriging, contextual classification methods. |
| Contact: Rasmus Larsen, building 321, (+45) 4525 3415, rl@imm.dtu.dk |
| Department: 002 Informatics and Mathematical Modelling |
| Course URL: http://www.imm.dtu.dk/courses/02503 |
| Keywords: Markov random fields, Bayesian image analysis, deformable models, geostatistics, orthogonal transformations |
| Updated: 14-01-2002 |
