A Depth-Based Dynamic Lightness Adjustment Power Saving Algorithm for AMOLED in Head-Mounted Displays

• Main Authors: Zun-Rong Yao, 姚樽融
• Other Authors: Shanq-Jang Ruan
• Format: Others
• Language: en_US
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/kr3jmj

碩士 === 國立臺灣科技大學 === 電子工程系 === 106 === Head-mounted display (HMD) is one of the popular consumer digital products that exploits the stereoscopic image to form the virtual reality (VR) experience based on the human visual system (HVS). Most of HMDs take the active-matrix organic light emitting diode (AMOLED) as the primary display panel because of its displaying superiorities. This thesis proposes a dynamic lightness adjustment algorithm to reduce the power consumption of AMOLED in HMD. The HVS has different degrees of attention for different regions of the image. By incorporating the depth information, which indicates how a pixel attractive to HVS, and the lightness of stereoscopic image, the proposed method can determine a lightness adjustment ratio. According to the experiments of two stereoscopic image datasets on AMOLED in HMD, the proposed method can achieve up to 44.26% of power-saving rate. In term of image quality, the proposed method provides mean visual saliency index of 0.962 and the time cost is 5.35 times faster than the existing power saving scheme.