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A Hardware-Friendly Fast VVC Test Zone Search Algorithm Using Machine Learning
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DOI：10.1109/LASCAS60203.2024.10506120.png)
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The Versatile Video Coding (VVC) currently stands as the state-of-the-art in video coding efficiency, but with the cost of substantial computational effort and, consequently, high energy consumption. This elevated energy usage poses a critical challenge, particularly for applications designed for battery-powered devices. A key component of the VVC is the Test Zone Search (TZS) algorithm, known for its demanding computational requirements. This paper addresses this issue by introducing a machine learning based solution for the TZS algorithm. Notably, this solution is hardware-friendly, leveraging Decision Trees that are straightforward to implement in hardware. The proposed solution achieved an average 86.98% reduction in TZS encoding time with a mere 0.45% impact on BD-BR.
Keyword:
Test Zone Search
Versatile Video Coding
Machine Learning
Decision Trees
Hardware-Friendly
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论文数:
10
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