Computational Image Processing

- Variational calculus
- Numerical solutions of PDEs
- Total variation methods
- Level-set representations
- Wavelet and scalespace analysis
- Image modelling and representation
- Multiscale image processing
- Applications to image processing problems such as denoising, deblurring, inpainting, segmentation, image difference, enhancement, gamut mapping, colour correction, demosaicing

Knowledge:
- The candidate is in the forefront of knowledge within the fields of selected computational image processing techniques
- The candidate can evaluate the expediency and application of variational image processing methods and processes in research and development projects
- The candidate has the ability to discuss and explain variational, wavelet and scale-space analytical methods

Skills:
- The candidate can formulate variational image processing problems using partial differential equations
- The candidate can implement numerical solutions to variational image processing problems

General competence:
- The candidate has the ability to communicate and lead discussions on recent research about computational image processing methods
- The candidate has the ability to evaluate and critique mechanisms for image modelling and representation

- Lectures
- Seminars
- Supervision

Compusory course work:
- On a given topic, prepare and give one seminar consisting of an introductory lecture (1-2 hours) followed by a conducted group discussion.
- Attend at least 75% of the lectures and seminars.