Deviation-Adjusted Bitrate Encoding for Video Segments
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Solution Overview
Problem
Existing video encoding techniques face challenges in efficiently encoding videos with high bitrate variability, leading to quality issues due to the use of static bitrates that do not adapt to the varying complexity of video content.
Innovation Solution
The implementation of deviation-adjusted bitrate encoding, which calculates a customized bitrate by analyzing the average bitrate and its deviation for each segment of a video file, allowing for adaptive encoding that matches the content complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If a static average bitrate is used for encoding the entire video file, then the encoding process is simple and fast, but video quality deteriorates in segments with high complexity due to insufficient bitrate allocation
Solution Approach 1:
The video file is divided into multiple segments, and each segment is analyzed independently to calculate its specific bitrate based on local complexity characteristics. This allows different bitrate allocations for different segments, improving overall video quality while maintaining manageable encoding complexity through localized processing.
Solution Approach 2:
Instead of applying a uniform bitrate across the entire video, the patent calculates a specific bitrate for each segment based on its local complexity metrics (such as motion magnitude, gradient magnitude, and color transformation). This local quality approach ensures that complex segments receive higher bitrates while simpler segments use lower bitrates, optimizing video quality efficiently.
2Manufacturing precision
If a higher static bitrate is used to ensure quality in complex segments, then video quality improves, but data transmission requirements increase unnecessarily for simpler segments
Solution Approach 1:
The patent implements dynamic bitrate allocation by calculating a specific bitrate for each video segment based on its complexity characteristics. This dynamic approach allows the bitrate to adapt to the actual content requirements of each segment, ensuring high quality where needed while reducing data transmission for simpler segments, thus resolving the contradiction between quality and data volume.
3Manufacturing precision
If segment-based encoding with individual bitrate calculation is implemented, then video quality improves by adapting to content complexity, but the encoding process becomes more computationally intensive
Solution Approach 1:
The patent performs preliminary analysis of video segments to calculate complexity metrics (motion magnitude, gradient magnitude, color transformation) before the actual encoding process. By pre-calculating the specific bitrate for each segment based on these metrics, the system avoids repeated computations during encoding, thus improving video quality while controlling computational resource usage through advance preparation.
Data Source
AI summary
Techniques and solutions are described for encoding digital video files, such as for streaming applications. Data associated with the digital video file forms a dataset that can be characterized by a measure of the dataset's center, such as an average, and a spread of the dataset, such as a deviation, with respective to a bitrate over a duration of the digital video file. The measure of center and spread are used to calculate a deviation-adjusted bitrate. A deviation adjusted bitrate can be calculated for the entire digital video file, or for particular subsets of the digital video file, such as for segments of a duration forming units of video streaming Disclosed techniques can provide various advantages, including using a reduced bitrate for video or video portions as compared with an average or static bitrate, for lower-complexity video, or using a higher bitrate for video or video portions for higher-complexity video.