Adaptive Motion Estimation Search Range for Video Coding
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Solution Overview
Problem
Current motion estimation and compensation schemes in video coding are inefficient for handling the increasing demands of video streaming and mobile videophone applications, requiring more efficient methods to manage pixel block motion estimation and compression.
Innovation Solution
A method for estimating pixel block motion by searching areas in frames to identify matching blocks with minimum error criteria, calculating motion vectors, and selecting a final motion vector based on error values, utilizing both full and adaptive search schemes to reduce computational complexity and improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a full search scheme is used to search the entire reference frame for matching blocks, then motion estimation accuracy is improved, but computational complexity increases significantly
Solution Approach 1:
The patent divides the reference frame into multiple regions or zones based on motion characteristics, and applies different search strategies to different regions. This segmentation allows the system to focus computational resources on areas requiring high precision while using simpler methods in other areas, thereby reducing overall computational complexity while maintaining motion estimation accuracy in critical regions.
Solution Approach 2:
The patent implements an adaptive search range mechanism that adjusts the search area size based on local motion characteristics. Instead of uniformly searching the entire reference frame, the system performs partial searches in regions with low motion activity and extended searches in regions with high motion activity. This partial action approach reduces computational complexity while maintaining accuracy where needed.
2Reliability
If a large search range is used to capture all possible motion vectors, then motion estimation reliability is improved, but processing time increases
Solution Approach 1:
The patent employs dynamic search range adjustment that adapts the search area size based on local motion characteristics and block characteristics. The search range is dynamically expanded or contracted during the motion estimation process, allowing the system to maintain reliability by extending searches when needed while reducing processing time by limiting searches in regions with predictable motion patterns.
Solution Approach 2:
The patent performs preliminary analysis of block characteristics and motion patterns before conducting the full motion estimation search. This preliminary action allows the system to pre-determine appropriate search ranges and strategies, avoiding unnecessary extensive searches and thereby reducing processing time while maintaining reliability through targeted searches in critical areas.
3Measurement precision
If multiple matching blocks are evaluated to ensure accuracy, then motion estimation precision is improved, but computational complexity increases
Solution Approach 1:
The patent applies different evaluation criteria and precision levels to different regions based on local characteristics. In regions with complex motion patterns or low texture, multiple matching blocks are evaluated with high precision. In regions with simple motion patterns or high texture, fewer blocks are evaluated with lower precision. This local quality approach maintains motion estimation precision where needed while reducing computational complexity in other areas.
Data Source
AI summary
A method and apparatus for estimating motion of a pixel block in a first frame, the method including searching a first area in a second frame to identify a first matching block that corresponds to the pixel block, the first matching block including a first error value that is a minimum of at least one error criteria between the pixel block and the first matching block, calculating a first motion vector associated with the first matching block. The method further including searching a second area in the second frame to identify a second matching block that corresponds to the pixel block, the second matching block including a second error value that is a minimum of the at least one error criteria between the pixel block and the second matching block, calculating a second motion vector associated with the second matching block and selecting a final motion vector between the first and second motion vectors based on the first and second error value.