Regional gradient dimming strategy for low-power silicon-based OLED microdisplays
In addressing the high power consumption of near-eye display devices,this paper introduces a region gradient dimming algorithm that adapts to the human eye's gaze point,informed by studies on hu-man visual characteristics.Initially,a central fovea-brightness masking experiment established the Just No-ticeable Difference(JND)threshold for the human eye.This data refined the traditional geometric optical path model of the eye gaze point,resulting in a model that aligns more closely with the eye's adaptive char-acteristics.The method significantly improved the efficiency of viewing angle calculations through a maxi-mum viewing angle discrimination approach.An enhanced contrast algorithm was then applied during im-age preprocessing to improve the display quality while preserving the image's average brightness.Utilizing the JND threshold and gaze point data,the algorithm applied both regional and global power consumption limits to the image,reducing power usage while maintaining subjective visual perception.The algorithm underwent validation on an FPGA hardware platform,demonstrating a reduction in display power con-sumption for silicon-based Organic Light Emitting Diode(OLED)microdisplays by up to 23.05%on the Kodak standard test set.This achievement suggests that the low-power requirements for silicon-based OLED microdisplays are achievable,offering insights for performance enhancements.
region gradient dimminggaze point adaptationmicrodisplaydisplay power consumptionJust Noticeble Difference(JND)
万方数据
维普
