Fang Lu (Hong Kong University of Science and Technology), “Digital Image and Video Processing Using Subpixel Rendering” (2011)

Fang Lu (Hong Kong University of Science and Technology), “Digital Image and Video Processing Using Subpixel Rendering”, Advisor: Oscar C. AU (2011)

In this thesis, the author is concerned about image/video processing using subpixel techniques to achieve superior sharpness for small LCD displays. Such a problem exists when a high resolution image or video is to be displayed on low resolution display terminals (i.e., Mobile). Signal processing theory shows that optimal decimation requires low-pass filtering with a suitable cut-off frequency followed by down-sampling. In doing so, people need to remove much useful image details causing blurring. Subpixel-based algorithm is a method that can potentially improve the apparent resolution of a down-scaled image by controlling individual subpixels rather than pixels.

The author starts by formulate subpixel-based down-sampling as optimization problems, MMDE(Min-Max Directional Error) and MMSE-SD (MMSE for subpixel-based down-sampling) based on different reconstruction models in spatial domain. To better understand what happens in subpixel-based algorithm, the author further proposes frequency domain analysis approach to explain why it is possible to achieve a higher apparent resolution using subpixel. Theoretical analysis shows that the cut-off frequency of the low-pass filter for subpixel-based decimation can be effectively extended beyond the Nyquist frequency using novel anti-aliasing filters. To compare the performance of pixel-based and subpixel-based methods, the author also proposes novel objective measures for apparent luminance resolution and chrominance distortion. Simulation results show that the proposed subpixel-based methods can give much sharper images compared with the conventional pixel-based methods.

For details, please access the full thesis or contact the author.