Optimizing RGBW Sub-pixel Rendering of a LCD based on Subjective and Objective Visual Assessment

碩士 === 國立臺灣科技大學 === 色彩與照明科技研究所 === 102 === The use of mobile devices such as smart phone and tablet computer has rapidly increased in recent years. The demand of LCD panels with higher resolution, luminance, color fidelity, and lower power consumption has been constantly growing. Conventional RGB-fi...

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Bibliographic Details
Main Authors: Shu-Yun Chang, 張書昀
Other Authors: Pei-Li Sun
Format: Others
Language:en_US
Published: 2014
Online Access:http://ndltd.ncl.edu.tw/handle/68820801832232298937
Description
Summary:碩士 === 國立臺灣科技大學 === 色彩與照明科技研究所 === 102 === The use of mobile devices such as smart phone and tablet computer has rapidly increased in recent years. The demand of LCD panels with higher resolution, luminance, color fidelity, and lower power consumption has been constantly growing. Conventional RGB-filter-based LCD suffers from low luminance. White sub-pixels therefore are added to enhance the luminance and so as to reduce power consumption. However there are many ways to perform RGBW Sub-pixel Rendering (SPR) for a LCD. The aim of this study is first to evaluate the effects of different SPR parameters, such as white extraction, chroma enhancement, sub-pixel layout and spatial filtering, on the perceptual image quality of representative RGBW SPR algorithms using a categorical judgement method. The results show sub-pixel layout is the key to achieve higher image quality. The luminance related sub-pixels (white and green) must be evenly distributed on the screen. Sub-pixel addressing is better than whole-pixel addressing. It will be great if a low resolution input image can be up-sampled to higher resolution using a supper resolution (or de-convolution) technology. Low pass spatial filtering is needed to reduce color aliasing. Chroma need to be enhanced mainly for bright colors. In terms of white extraction, min(R, G, B) and relative luminance can preserve colorfulness and brightness of saturate colors respectively. The results are used to derive a new SPR algorithm and the spatial filter was optimized by S-CIELAB metric. The proposed algorithm outperforms the benchmark algorithms (PenTile RGBW and MS-RGBW) in the second psycho-visual experiment using paired comparison method. The results also suggest slight image sharpening would further improve its perceptual image quality.