Power-Constrained RGB-to-RGBW Conversion for Emissive Displays: Optimization-Based Approaches

• Published in: IEEE transactions on circuits and systems for video technology Vol. 26; no. 10; pp. 1821 - 1834
• Main Authors: Chul Lee, Monga, Vishal
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.10.2016; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Clean energy; Color; Color distortion; Computer simulation; Conversion; Distortion; emissive display; Emissivity; Image color analysis; low-power image processing; Optimization; Power consumption; Power demand; power management; red-green–blue (RGB)-to-red-green–blue-white (RGBW) conversion; RGBW display; State of the art; Table lookup
• ISSN: 1051-8215; 1558-2205
• DOI: 10.1109/TCSVT.2015.2475915

We propose an optimization-based power-constrained red-green-blue (RGB)-to-red-green-blue-white (RGBW) conversion algorithm for emissive RGBW displays. We measure the perceived color distortion using a color difference model in a perceptually uniform color space, and compute the power consumption for displaying an RGBW pixel on an emissive display. The central contribution of this paper is to formulate the optimization problem to minimize the color distortion subject to a constraint on the power consumption. Subsequently, we solve the optimization problem efficiently to convert an image in real time. Furthermore, based on the properties of the human visual system, we extend the proposed algorithm to image-dependent conversion that can preserve spatial detail in an input image. The simulation results show that the proposed algorithm provides a significantly less color distortion than the conventional methods, while providing a graceful tradeoff with the amount of power consumed. Specifically, it is shown that the power consumption can be reduced by up to 20%, while providing about 50% less color distortion than the conventional algorithms. In addition, a subjective evaluation on a real RGBW display is performed, which reveals the merits of the proposed image-dependent conversion for improving the perceptual quality over state-of-the-art techniques.