Characteristic-Based Video Processing for Bandwidth Reduction
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Solution Overview
Problem
High-definition video surveillance systems face challenges due to high bandwidth and storage demands, as HD video bitstreams require significant bandwidth for transmission and storage, limiting their large-scale deployment.
Innovation Solution
The implementation of characteristic-based video processing, which involves determining characteristics in video regions independent of others, classifying them, and encoding using parameter sets associated with these classes to reduce bitrate without significant information loss, allowing for customizable quality levels based on application scenarios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If HD video encoding is used to capture more information, then video quality and information capture are improved, but bandwidth and storage requirements increase significantly
Solution Approach 1:
The video picture is divided into multiple independent regions, each processed separately with different encoding parameters. This allows selective application of high-quality encoding only to important regions while using lower-quality encoding for less important regions, thereby reducing overall bandwidth and storage requirements while maintaining acceptable video quality for critical areas.
Solution Approach 2:
Different quality levels are applied to different regions of the video picture based on their importance. Important regions (such as those containing objects of interest) are encoded with higher quality parameter sets, while less important regions are encoded with lower quality parameter sets. This local differentiation maintains measurement precision where needed while reducing the quantity of data overall.
2Measurement precision
If high bitrate encoding is used for HD video, then video quality is improved, but transmission and storage costs increase
Solution Approach 1:
The video stream is segmented into multiple regions with different quality requirements. By processing each region independently with appropriate quality levels, the system avoids applying high-bitrate encoding uniformly across the entire video, thereby reducing transmission and storage costs while maintaining coding quality where it matters most.
Solution Approach 2:
Different parameter sets are applied to different video regions based on their importance. This dynamic parameter adjustment allows the system to optimize the balance between coding quality and resource consumption by using higher quality parameters for important regions and lower quality parameters for less important regions, thereby reducing overall energy loss in the form of bandwidth and storage costs.
Data Source
AI summary
A method and apparatus for characteristic-based video processing include: in response to receiving a region of a picture of a video sequence, determining a characteristic in the region, the region being independent of other regions of the picture for video coding; determining a class associated with the region based on the characteristic, the class being selected from a plurality of classes; and encoding the region using a parameter set associated with the class, the parameter set being selected from a plurality of parameter sets for video coding at different quality levels.