Segmentation-Based Video Prediction Coding for Bitrate Optimization
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Solution Overview
Problem
Existing video compression schemes face a trade-off between prediction quality and bitrate, where finding the best prediction often increases bitrate, and reducing bitrate can result in suboptimal prediction, affecting video quality.
Innovation Solution
The method involves assigning video blocks to segments based on motion, color, or spatial information, determining prediction elements for each segment, and applying these elements to encode and decode video signals efficiently, thereby optimizing prediction quality and bitrate.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If motion estimation search algorithms search for the best matching region in reference frames, then prediction quality is improved, but bitrate increases due to encoding more prediction information
Solution Approach 1:
The patent divides the video frame into multiple segments based on motion characteristics, and applies different prediction strategies to different segments. This segmentation allows the system to achieve high prediction quality for complex motion regions while using simpler prediction for uniform regions, thereby reducing overall bitrate while maintaining prediction accuracy.
Solution Approach 2:
The patent applies different prediction precision levels to different spatial regions based on their motion characteristics. Regions with complex motion receive more sophisticated prediction treatment, while regions with simple motion use simpler prediction methods. This local differentiation optimizes the balance between prediction quality and bitrate efficiency.
2Quantity of substance
If bitrate is decreased to reduce bandwidth consumption, then bandwidth efficiency is improved, but prediction quality deteriorates resulting in suboptimal video compression
Solution Approach 1:
By segmenting the video content and applying adaptive prediction strategies, the patent achieves efficient bitrate utilization. Complex regions receive appropriate prediction resources while simple regions consume minimal bits, optimizing the overall prediction quality per bitrate ratio.
Solution Approach 2:
The patent dynamically adjusts prediction parameters such as motion vector precision and search range based on local content characteristics. This parameter adaptation allows the system to maintain high prediction quality in critical regions while reducing bitrate in less critical regions, achieving optimal compression efficiency.
3Measurement precision
If more prediction information is encoded to achieve better prediction, then video quality is improved, but device complexity increases due to more processing requirements
Solution Approach 1:
The patent segments video content and applies different processing complexities to different segments. This allows high-quality prediction processing to be applied only where necessary, reducing overall computational complexity while maintaining video quality in critical regions.
Solution Approach 2:
The patent applies complex prediction algorithms locally to regions that benefit most from them, while using simpler algorithms in other regions. This localized approach to quality optimization reduces overall processing complexity while maintaining high video quality where it matters most.
Data Source
AI summary
A method for encoding a video signal having at least one frame with a plurality of blocks includes assigning at least some of the plurality of blocks to a segment, determining at least one prediction element for the segment using a processor, applying the at least one prediction element to a first block and at least some of the other blocks in the segment and encoding the first block and the other blocks in the segment.