Exploiting Human Color Discrimination for Memory- and Energy-Efficient Image Encoding in Virtual Reality

• Nisarg Ujjainkar, University of Rochester


• Ethan Shahan, University of Rochester


• Kenneth Chen, New York University


• Budmonde Duinkharjav, New York University


• Qi Sun, New York University


• Yuhao Zhu, University of Rochester

Our algorithm takes a tile of pixels and their corresponding discrimination ellipsoid parameters, and generate an adjusted pixel tile, which then goes through existing BD encoding.

Abstract

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Virtual Reality (VR) has the potential of becoming the next ubiquitous computing platform. Continued progress in the burgeoning field of VR depends critically on an efficient computing substrate. In particular, DRAM access energy is known to contribute to a significant portion of system energy. Today’s framebuffer compression system alleviates the DRAM traffic by using a numerically lossless compression algorithm. We observe that being numerically lossless is unnecessary to preserve perceptual quality for users. This paper proposes a perceptually lossless, but numerically lossy, system to compress DRAM traffics. Our idea builds on top of long-established psychophysical studies that humans cannot discriminate colors that are close to each other. The discrimination ability becomes even weaker (i.e., more colors are perceptually undistinguishable) in our peripheral vision. Leveraging the color discrimination (in)ability, we propose an algorithm that adjusts pixel colors to minimize the bit encoding cost without introducing visible artifacts. The algorithm is coupled with lightweight architectural support that, in real-time, reduces the DRAM traffic by 66.9% and outperforms existing framebuffer compression mechanisms by up to 20.4%. Psychophysical studies on human participants show that our system introduce little to no perceptual fidelity degradation.

@inproceedings{
 ujjainkar2024exploiting, 
 author = {Ujjainkar, Nisarg and Shahan, Ethan and Chen, Kenneth and Duinkharjav, Budmonde and Sun, Qi and Zhu, Yuhao}, 
 title = {Exploiting Human Color Discrimination for Memory- and Energy-Efficient Image Encoding in Virtual Reality}, 
 year = {2024}, 
 url = {https://doi.org/10.1145/3617232.3624860}, 
 booktitle = {Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 1}, 
 pages = {166–180}, 
 numpages = {15}, 
 series = {ASPLOS '24}
 }

Links

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