Motion Estimation Search Pattern Selection for Video Coding
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Solution Overview
Problem
Existing video coding standards face high computational complexity in motion estimation, particularly with the use of full search algorithms, which is exacerbated by the need for dynamic bandwidth adaptation in wireless networks and variable motion content, leading to inefficient data compression and quality degradation.
Innovation Solution
A system and method for dynamically selecting a block matching algorithm based on video content and available bandwidth, using a motion classifier weight factor, link bandwidth weight factor, and probability factor to choose between different search patterns such as Non-uniform hierarchical, Variable hexagon, Fixed 3-step small hexagon, Variable diamond, and Fixed 3-step small diamond searches, optimizing motion estimation while reducing computational complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If full search algorithm is employed for motion estimation, then video compression performance is improved, but computational complexity increases significantly
Solution Approach 1:
The patent dynamically adjusts the motion estimation search algorithm based on motion magnitude detection. When low motion is detected, a reduced search range algorithm is applied; when high motion is detected, a full or extended search algorithm is used. This dynamic adaptation resolves the contradiction by matching computational effort to actual motion content, improving compression performance only when necessary while reducing complexity during static scenes.
Solution Approach 2:
The patent changes the search parameter (search range) based on detected motion magnitude. The search range is adjusted as a variable parameter rather than being fixed, allowing the system to optimize between compression performance and computational complexity by modifying the search extent according to actual video content characteristics.
2Manufacturing precision
If larger block structures (64×64 CTUs) are used in HEVC, then data compression ratio is improved, but computational complexity increases dramatically
Solution Approach 1:
The patent segments the large 64×64 coding tree units into smaller motion estimation blocks and applies different motion estimation algorithms to different segments based on local motion characteristics. This segmentation allows the system to maintain the compression benefits of large blocks while reducing the computational burden by applying simplified algorithms in low-motion regions and full algorithms only where necessary.
Solution Approach 2:
The patent applies different quality levels of motion estimation to different regions within the video frame based on local motion magnitude. High-motion regions receive full search algorithm treatment for optimal compression, while low-motion regions receive reduced search range treatment. This local quality differentiation resolves the contradiction by concentrating computational resources only where they provide actual compression benefit.
3Productivity
If adaptive search patterns are used based on motion content, then motion estimation efficiency is improved, but processing requirements increase due to motion analysis
Solution Approach 1:
The patent performs partial motion analysis by detecting only the magnitude of motion rather than full motion vectors or detailed motion patterns. This partial action approach provides sufficient information to select appropriate search algorithms without the processing overhead of complete motion analysis, thereby improving motion estimation efficiency while limiting the increase in processing requirements.
Data Source
AI summary
Systems and methods for motion estimation for video encoding are described. The method observes the motion from the previous frames of the video uses the same for predicting search pattern and classifying the motion for the current frame. The motion in the video is predicted by calculating the Temporal Redundancy Achieved for previous frames and the Block Movement Factor in the previous frame. The method also considers the available bandwidth for choosing the search pattern especially, in the case of video streaming in wireless mobile ad hoc networks.