Visual Perception Adaptive Image Processing for HD Microdisplay

With the development of 5G networks, a new wave of development is ushered in the field of virtual reality (VR). The small physical size, lightweight, low power consumption, and high brightness make microdisplays the core components of VR. In order to improve the user's immersive experience and...

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Bibliographic Details
Published in:SID International Symposium Digest of technical papers 2020-07, Vol.51 (S1), p.31-34
Main Authors: Chen, Yuansheng, Song, Yuansheng, Chen, Wendong, Mu, Tingzhou, Ji, Yuan
Format: Article
Language:English
Subjects:
adaptive
Compression ratio
Core making
Data transmission
Eye movements
Image compression
Image processing
Image transmission
microdisplay
Power consumption
Rendering
Virtual reality
Visual perception
Visual perception driven algorithms
Wireless networks
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Summary:With the development of 5G networks, a new wave of development is ushered in the field of virtual reality (VR). The small physical size, lightweight, low power consumption, and high brightness make microdisplays the core components of VR. In order to improve the user's immersive experience and reduce the screen window effect, microdisplays are required to have higher pixel density and faster refresh speeds. However, this demand results in a large amount of data transmission and poor real‐time rendering of image information. When the human eye observes an image, the gaze point changes due to the interest of the viewer. To solve this problem, we propose an image compression algorithm based on visual perception adaptation to reduce data transmission bandwidth. The experimental results show that when sight distance is 2, the maximum comprehensive compression ratio is 42.834, the minimum comprehensive compression ratio is 11.415, the minimum clock frequency is 17.033MHz, and the maximum clock frequency is 63.916MHz. The algorithm effectively reduces the data transmission bandwidth and meets the real‐time rendering of VR application, and the rendering effect is good.
ISSN:0097-966X
2168-0159
DOI:10.1002/sdtp.13744