Emerging organic light-emitting diode (OLED)-based displays obviate external lighting; and consume drastically different power when displaying different colors, due to their emissive nature. This creates a pressing need for OLED display power models for system energy management, optimization as well as energyefficient GUI design, given the display content or even the graphical user interface (GUI) code. In this work, we present a comprehensive treatment of power modeling of OLED displays, providing models that estimate power consumption based on pixel, image, and code, respectively. These models feature various tradeoffs between computation efficiency and accuracy so that they can be employed in different layers of a mobile system. We validate the proposed models using a commercial QVGA OLED module. For example, our statistical learning-based image-level model reduces computation by 1600 times while keeping the error below 10%, compared to the more accurate pixel-level model.

In this paper, we show how tone mapping techniques can be used to dynamically increase the image brightness, thus allowing the LCD backlight levels to be reduced. This saves significant power as the majority of the LCD’s display power is consumed by its backlight. The Gamma function (or equivalent) can be efficiently implemented in smartphones with minimal resource cost. We describe how we overcame the Gamma function’s non-linear nature by using adaptive thresholds to apply different Gamma values to images with differing brightness levels. These adaptive thresholds allow us to save significant amounts of power while preserving the image quality. We implemented our solution on a laptop and two Android smartphones. Finally, we present measured analytical results for two different games (Quake III and Planeshift), and user study results (using Quake III and 60 participants) that shows that we can save up to 68 % of the display power without significantly affecting the perceived gameplay quality.