Video Encoding String Prediction Using Matching and Flip Patterns
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Solution Overview
Problem
The existing video encoding methods face challenges in achieving optimal string prediction due to misalignment in bit estimation and insufficient string vector candidates, which affect the compression rate.
Innovation Solution
The method involves determining a current string in a coding unit by searching for reference matching pixels and applying various flip patterns to adjust pixel positions, comparing costs, and selecting the optimal prediction based on matching patterns to improve string prediction accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If string prediction is performed with conventional methods, then the encoding process can proceed, but the bit estimation is misaligned and string vector candidates are insufficient, affecting compression rate
Solution Approach 1:
The patent divides the string prediction process into multiple stages: first generating initial string vector candidates through conventional methods, then segmenting and refining these candidates by evaluating multiple matching patterns (horizontal, vertical, diagonal) and flip patterns. This segmentation allows systematic exploration of candidate vectors while maintaining alignment with bit estimation requirements.
Solution Approach 2:
The patent performs preliminary actions by pre-generating a comprehensive list of string vector candidates before final selection. It evaluates multiple matching patterns and flip patterns in advance to create a robust candidate set, ensuring that the final string vector selection is well-aligned with bit estimation and maximizes compression efficiency.
2Productivity
If more string vector candidates are generated to improve prediction accuracy, then compression rate improves, but the complexity of the encoding process increases
Solution Approach 1:
The patent applies local quality by evaluating different matching patterns (horizontal, vertical, diagonal) and flip patterns selectively based on the specific characteristics of each coding unit and string. Not all patterns are applied uniformly throughout the entire image, but rather tailored to local regions where they are most beneficial, optimizing compression while controlling overall complexity.
Solution Approach 2:
The patent employs partial action by evaluating multiple matching patterns and flip patterns to generate a comprehensive set of string vector candidates, then selecting only the optimal candidates for final encoding. This partial evaluation approach ensures sufficient candidates are generated for high compression rates while avoiding the excessive complexity of exhaustively evaluating all possible patterns in all regions.
Data Source
AI summary
The present disclosure relates to systems and methods for video encoding. The systems may determine a current string in a coding unit (CU) of an image frame. The current string may include one or more pixels. The systems may determine, based on a first pixel in the current string, a reference matching pixel of the first pixel by searching a searching area. The searching area may include a plurality of matching pixels The systems may determine, based on the reference matching pixel and matching patterns, a count of matching pixels in each of a plurality of groups, corresponding to the matching patterns, of the current string. The systems may further determine, based on counts of matching pixels in the plurality of groups corresponding to the matching patterns, a target prediction of the current string.