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VMAF Video Quality Metric Accelerator
Video encoding and delivery optimizations play a critical role in modern video streaming service market. Optimizations such as content-aware encoding and multi-codec usage strategies increase the service’s QoE and reduce the cost of storing and delivering video so that the streaming services stay competitive in the market.
You can make these optimizations by measuring the visual quality of the transcoded output to ensure that the data used to encode is not wasted.
VMAF quality metric, which mimics the human visual system, has been widely used to measure quality. But, VMAF is based on ML(Machine Learning) and has a very high computational complexity, making it computing resource intensive and slow.
Pulsar-VMAF is a fixed functional hardware accelerator IP to offer the highest computing efficiency for measuring VMAF Video Quality Metric. Compared to software VMAF on CPU, Pulsar-VMAF outperforms and provides faster time to result.
You can make these optimizations by measuring the visual quality of the transcoded output to ensure that the data used to encode is not wasted.
VMAF quality metric, which mimics the human visual system, has been widely used to measure quality. But, VMAF is based on ML(Machine Learning) and has a very high computational complexity, making it computing resource intensive and slow.
Pulsar-VMAF is a fixed functional hardware accelerator IP to offer the highest computing efficiency for measuring VMAF Video Quality Metric. Compared to software VMAF on CPU, Pulsar-VMAF outperforms and provides faster time to result.
View VMAF Video Quality Metric Accelerator full description to...
- see the entire VMAF Video Quality Metric Accelerator datasheet
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Block Diagram of the VMAF Video Quality Metric Accelerator IP Core
Video Demo of the VMAF Video Quality Metric Accelerator IP Core
IP evaluation is available at https://github.com/bluedot-io/Pulsar-VMAF