High contrast ratio (CR) enables a display system to faithfully reproduce the real objects. However, achieving high contrast, especially high ambient contrast (ACR), is a challenging task. In this dissertation, two display systems with high CR are discussed: high ACR augmented reality (AR) display and high dynamic range (HDR) display. For an AR display, we improved its ACR by incorporating a tunable transmittance liquid crystal (LC) film. The film has high tunable transmittance range, fast response time, and is fail-safe. To reduce the weight and size of a display system, we proposed a functional reflective polarizer, which can also help people with color vision deficiency. As for the HDR display, we improved all three aspects of the hardware requirements: contrast ratio, color gamut and bit-depth. By stacking two liquid crystal display (LCD) panels together, we have achieved CR over one million to one, 14-bit depth with 5V operation voltage, and pixel-by-pixel local dimming. To widen color gamut, both photoluminescent and electroluminescent quantum dots (QDs) have been investigated. Our analysis shows that with QD approach, it is possible to achieve over 90% of the Rec. 2020 color gamut for a HDR display. Another goal of an HDR display is to achieve the 12-bit perceptual quantizer (PQ) curve covering from 0 to 10,000 nits. Our experimental results indicate that this is difficult with a single LCD panel because of the sluggish response time. To overcome this challenge, we proposed a method to drive the light emitting diode (LED) backlight and the LCD panel simultaneously. Besides relatively fast response time, this approach can also mitigate the imaging noise. Finally yet importantly, we improved the display pipeline by using a HDR gamut mapping approach to display HDR contents adaptively based on display specifications. A psychophysical experiment was conducted to determine the display requirements.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd-6700 |
| Date | 01 January 2017 |
| Creators | Zhu, Ruidong |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations |
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