Inline Downscaling Hardware for Video Encoding Latency
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Solution Overview
Problem
Ultra-low latency video encoding networks face significant latency issues due to the need for full resolution passes, which increase computational load and power consumption, especially during scene changes, and conventional external downscaling methods further exacerbate these problems.
Innovation Solution
Implementing inline downscaling hardware within the encoder pipeline to perform on-the-fly downsampling of video frames, reducing the computational load and power consumption by downsampling frames internally without the need for external memory, and using dedicated hardware to convert between different color subsampling schemes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If full resolution passes are used for video encoding, then encoding quality is improved, but latency and computational load increase significantly
Solution Approach 1:
The encoding process is divided into two distinct passes: a first pass at reduced resolution to gather statistics, and a second pass at full resolution to encode final frames. This segmentation allows the system to separate quality-critical operations from speed-critical operations, reducing overall latency while maintaining encoding quality.
Solution Approach 2:
Statistics such as quantization parameters and motion complexity are pre-calculated during a first pass at reduced resolution before the actual full-resolution encoding begins. This preliminary action prepares encoding parameters in advance, enabling faster full-resolution encoding without sacrificing quality.
2Manufacturing precision
If full resolution passes are used for video encoding, then encoding quality is improved, but power consumption increases
Solution Approach 1:
The encoding workload is segmented into a low-power first pass at reduced resolution and a focused second pass at full resolution. By performing statistics gathering at lower resolution, the system significantly reduces the computational power required for the initial analysis phase.
Solution Approach 2:
The first pass uses partial resolution (reduced quality) to gather sufficient statistics for encoding, which is excessive for final quality but necessary for speed. This partial action at reduced resolution reduces power consumption while still providing adequate data for the second pass.
3Volume of moving object
If external downscaling methods are used, then frame size is reduced, but device complexity and memory requirements increase
Solution Approach 1:
The downscaling function is merged directly into the encoder pipeline as an integrated component. Rather than using separate external downscaling hardware or software, the encoder incorporates downscaling capabilities internally, reducing system complexity and eliminating the need for external memory interfaces.
Solution Approach 2:
The encoder is designed with multi-functionality, combining both encoding and downscaling operations within a single device. This universal design eliminates the need for separate downscaling hardware and reduces overall system complexity while maintaining the ability to reduce frame size efficiently.
Data Source
AI summary
Techniques related to video encoding include inline downscaling hardware in multi-pass encoding.