Gamut extension algorithm development and evaluation for the mapping of standard image content to wide-gamut displays

Wide-gamut display technology has provided an excellent opportunity to produce visually pleasing images, more so than in the past. However, through several studies, including Laird and Heynderick, 2008, it was shown that linearly mapping the standard sRGB content to the gamut boundary of a given wide-gamut display may not result in optimal results. Therefore, several algorithms were developed and evaluated for observer preference, including both linear and sigmoidal expansion algorithms, in an effort to define a single, versatile gamut expansion algorithm (GEA) that can be applied to current display technology and produce the most preferable images for observers. The outcome provided preference results from two displays, both of which resulted in large scene dependencies. However, the sigmoidal GEAs (SGEA) were competitive with the linear GEAs (LGEA), and in many cases, resulted in more pleasing reproductions. The SGEAs provide an excellent baseline, in which, with minor improvements, could be key to producing more impressive images on a wide-gamut display

High dynamic range display systems

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

Evaluation of the color image and video processing chain and visual quality management for consumer systems

With the advent of novel digital display technologies, color processing is increasingly becoming a key aspect in consumer video applications. Today’s state-of-the-art displays require sophisticated color and image reproduction techniques in order to achieve larger screen size, higher luminance and higher resolution than ever before. However, from color science perspective, there are clearly opportunities for improvement in the color reproduction capabilities of various emerging and conventional display technologies. This research seeks to identify potential areas for improvement in color processing in a video processing chain. As part of this research, various processes involved in a typical video processing chain in consumer video applications were reviewed. Several published color and contrast enhancement algorithms were evaluated, and a novel algorithm was developed to enhance color and contrast in images and videos in an effective and coordinated manner. Further, a psychophysical technique was developed and implemented for performing visual evaluation of color image and consumer video quality. Based on the performance analysis and visual experiments involving various algorithms, guidelines were proposed for the development of an effective color and contrast enhancement method for images and video applications. It is hoped that the knowledge gained from this research will help build a better understanding of color processing and color quality management methods in consumer video

Print engine color management using customer image content

The production of quality color prints requires that color accuracy and reproducibility be maintained to within very tight tolerances when transferred to different media. Variations in the printing process commonly produce color shifts that result in poor color reproduction. The primary function of a color management system is maintaining color quality and consistency. Currently these systems are tuned in the factory by printing a large set of test color patches, measuring them, and making necessary adjustments. This time-consuming procedure should be repeated as needed once the printer leaves the factory. In this work, a color management system that compensates for print color shifts in real-time using feedback from an in-line full-width sensor is proposed. Instead of printing test patches, this novel attempt at color management utilizes the output pixels already rendered in production pages, for a continuous printer characterization. The printed pages are scanned in-line and the results are utilized to update the process by which colorimetric image content is translated into engine specific color separations (e.g. CIELAB-\u3eCMYK). The proposed system provides a means to perform automatic printer characterization, by simply printing a set of images that cover the gamut of the printer. Moreover, all of the color conversion features currently utilized in production systems (such as Gray Component Replacement, Gamut Mapping, and Color Smoothing) can be achieved with the proposed system