Live Stream Resolution Switching for Compression Artifact Control
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Solution Overview
Problem
Video streaming quality suffers during high motion, high detail, high contrast, scene cuts, and camera blur segments due to excessive compression, leading to visible degradation, and existing methods cannot dynamically adjust encoding parameters without increasing bitrate, which is often limited by bandwidth constraints.
Innovation Solution
A video streaming system that assesses quality on a segment-by-segment basis using machine learning algorithms to dynamically switch resolution, adjusting encoding to maintain consistent bitrate and reduce artifacts, with parallel or serial encoding processes to optimize video quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If video compression is increased to maintain bandwidth limitations, then bandwidth usage is controlled, but video quality degrades with visible artifacts
Solution Approach 1:
The video stream is divided into individual segments that are independently assessed and processed. Each segment is evaluated for quality metrics and processed accordingly, allowing selective application of different processing strategies to different portions of the video content based on their specific quality requirements.
Solution Approach 2:
Different quality levels and processing approaches are applied to different video segments based on their specific characteristics. High-quality processing is applied where needed, while acceptable quality is maintained elsewhere, optimizing the overall balance between bandwidth usage and perceived video quality across the entire stream.
2Manufacturing precision
If encoding parameters are changed to improve video quality, then video quality improves, but device complexity increases
Solution Approach 1:
The system dynamically adjusts encoding parameters and resolution settings in real-time based on the assessed quality of each video segment. Rather than using fixed encoding parameters throughout, the system adaptively modifies settings such as resolution and bitrate for different segments, optimizing video quality while managing encoding complexity through automated quality assessment.
Solution Approach 2:
The system changes encoding parameters such as resolution and bitrate based on the assessed quality of video segments. By dynamically adjusting these parameters according to actual video content characteristics and quality metrics, the system improves overall video quality while avoiding unnecessary complexity in encoding configurations.
3Manufacturing precision
If resolution is increased to reduce compression artifacts, then video quality improves, but bandwidth consumption increases
Solution Approach 1:
The video stream is segmented and each segment is independently assessed for quality. This allows the system to identify specific segments that require higher resolution processing to reduce compression artifacts, while maintaining lower resolution in segments where quality is already acceptable, thereby optimizing bandwidth usage.
Solution Approach 2:
Higher resolution is applied locally to specific video segments that require it to reduce compression artifacts, rather than uniformly increasing resolution across the entire video stream. This targeted approach improves video quality where needed while minimizing overall bandwidth consumption.
Data Source
AI summary
A method for reducing artifacts in streaming video implemented by a computing device involves determining whether a video quality assessment score for a current segment of a channel of a video stream with a first resolution and a first bit rate meets a quality threshold, replacing the current segment with a replacement segment with a lower resolution than the first resolution, in response to the current segment failing to meet the quality threshold, and publishing the replacement segment at the first bit rate as part of the video stream.