Nowdays, multimedia data are ubiquitous. You take pictures and videos with your camera and camcorders everyday. Have you thought about how you can judge the perceptual quality of the pictures and videos you made and how good your camera/camcorder is? In this project, you will develop algorithms for image and video quality assessment, especially for the purpose of assessing performance of digital cameras and camcorders. The following aspects of perceptual quality are of interests: blur/sharpness, noise, color fidelity, resolution, geometric distortions, blockiness, ringing, frame dropping and freezing, and so on. There are three types of quality assessment modes according to the availability of a reference: no-reference (NR), reduced-reference (RR) and full-reference (FR).
You can choose to work on implementation of objective image and video quality assessment algorithms, comparison of different algorithms, and/or collection of subjective quality evaluation of human observers (based on some software supporting such data collection). For color fidelity assessment, you need to work with some special devices (spectrometer, monochromat, video capturing devices or some selected camcorders).
If you choose to implement objective image and video quality assessment algorithms, they should be implemented in MATLAB. Some efficient sensitive algorithms may need to be implemented as C-MEX files.
Digital image processing (essential)
Probability theory and statistics (essential)
Basic linear algebra (matrix computation) (essential)
Programming exprience with MATLAB (essential)
Numerical algorithms (curve fitting, optimization, etc.) (advantageous)
Multimedia coding / Computer vision (advantageous)
Knowledge on color science, camera system and photography (advantageous)
Programming experience with C/C++ (advantageous)