Hardware acceleration of video quality metrics

Deepa Palamadai Sundar; Visala Vaduganathan; Xing C. Chen

doi:10.1117/12.2569302

21 August 2020 Hardware acceleration of video quality metrics

Deepa Palamadai Sundar, Visala Vaduganathan, Xing C. Chen

Proceedings Volume 11510, Applications of Digital Image Processing XLIII; 115100I (2020) https://doi.org/10.1117/12.2569302
Event: SPIE Optical Engineering + Applications, 2020, Online Only

Abstract

Quality Metrics (QM) provide an objective way to measure perceived video quality. These metrics are very compute intensive and are currently done in software. In this paper, we propose an accelerator that can compute metrics like single scale and multi-scale Structural Similarity Index (SSIM, MS_SSIM) and Visual Information Fidelity (VIF). The proposed accelerator offers an energy efficient solution compared to traditional CPUs. It improves memory bandwidth utilization by computing multiple Quality metrics simultaneously.

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Deepa Palamadai Sundar, Visala Vaduganathan, and Xing C. Chen "Hardware acceleration of video quality metrics", Proc. SPIE 11510, Applications of Digital Image Processing XLIII, 115100I (21 August 2020); https://doi.org/10.1117/12.2569302

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