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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.
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