Video Encoding Pre-Analysis for Content-Aware Bitrate Control
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Solution Overview
Problem
Existing video encoding techniques struggle to balance compression and fidelity effectively, particularly in LCEVC, where parts of a video with varying information density require tailored encoder parameters to meet specific requirements.
Innovation Solution
A method for determining encoder parameters through pre-analysis, including down-sampling video frames and generating detail perception metrics like edge detection and motion metrics, to optimize encoding for LCEVC, ensuring intelligent resource prioritization and fidelity in varying video content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of substance
If encoder parameters are chosen to improve compression, then bit rate is reduced, but perceived quality of reconstructed video deteriorates
Solution Approach 1:
The patent applies local quality by analyzing different regions of video frames and assigning different encoder parameters based on local content characteristics. Detail perception metrics are calculated for different blocks, and encoder parameters are adjusted locally to preserve quality in important regions while allowing higher compression in less important regions, thus resolving the contradiction between overall compression and perceived quality.
Solution Approach 2:
The patent performs pre-analysis of video content before encoding to determine detail perception metrics and edge detection metrics. This preliminary action allows the encoder to be configured intelligently based on actual video content characteristics, enabling optimal balance between compression and quality for each specific video rather than using fixed parameters.
2Manufacturing precision
If encoder parameters are configured to prioritize fidelity in high information density regions, then perceived quality improves, but bit rate increases
Solution Approach 1:
The patent identifies high information density regions using edge detection metrics and detail perception metrics, then applies higher quality encoding only to these specific regions. Low information density regions are encoded with higher compression. This selective approach improves perceived quality where it matters most while minimizing overall bit rate increase.
3Manufacturing precision
If pre-analysis is performed to determine encoder parameters intelligently, then compression-fidelity balance improves, but computational load increases
Solution Approach 1:
The patent divides the video frame into multiple blocks and calculates detail perception metrics for each block separately. This segmentation allows the computationally intensive pre-analysis to be distributed and performed in parallel, reducing overall computational load while maintaining the ability to optimize encoder parameters intelligently for each region.
Data Source
AI summary
A method for determining an encoder parameter for encoding an input video comprising a sequence of video frames, the input video having a first resolution, the method comprising: obtaining a first and a second video frame of the input video, wherein the second video frame follows the first video frame in the sequence of video frames; down-sampling the first and second frames to a second resolution to obtain a first and a second down-sampled video frame; generating a detail perception metric based on the first and second down-sampled video frames; determining, based on the detail perception metric, an encoder parameter for encoding the second video frame, wherein the detail perception metric comprises an edge detection metric based on the second down-sampled frame and a motion metric based on a difference between the first and second down-sampled frames.