Transform Block Size Rules for Merge-Efficient Video Coding
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Solution Overview
Problem
Existing video coding standards face challenges in efficiently managing merge candidates and transform block sizes, leading to suboptimal video quality and increased bandwidth usage.
Innovation Solution
Implementing adaptive loop filters based on video block depth and geometric partitioning modes, along with format rules for merge candidates and transform block sizes, to enhance video coding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the maximum transform block size is restricted to be equal to or less than the maximum CTU size, then the video coding efficiency is improved, but the flexibility in transform block size selection is reduced
Solution Approach 1:
The patent applies parameter changes by establishing a direct relationship between the maximum transform block size and maximum CTU size through format rules. This parameter constraint ensures that transform blocks do not exceed CTU boundaries, improving coding efficiency while maintaining adaptability through predefined size relationships rather than arbitrary size selections.
2Loss of substance
If merge candidates are selectively included or excluded in the bitstream representation, then the bandwidth usage is reduced, but the video quality may deteriorate
Solution Approach 1:
The patent applies local quality by selectively including or excluding merge candidates in the bitstream representation based on specific format rules. This selective inclusion mechanism allows the system to optimize bandwidth usage by transmitting only necessary merge candidate information, while maintaining video quality through intelligent selection criteria that preserve essential coding information.
3Manufacturing precision
If adaptive loop filters are applied based on video block depth, then the video quality is improved, but the processing complexity increases
Solution Approach 1:
The patent applies parameter changes by using video block depth as a controlling parameter for adaptive loop filter application. This parameter-based approach allows the system to adjust filter characteristics according to the hierarchical structure of video blocks, improving video quality while managing processing complexity through a systematic parameter-driven framework.
Data Source
AI summary
A visual media processing method includes performing a conversion between a current video block of a visual media data and a bitstream representation of the current video block. The bitstream representation is configured according to a format rule that specifies that a syntax element is selectively included or excluded in the bitstream representation indicative of a maximum number of merge candidates for a coding tool, thereby indicating whether the coding tool is enabled or disabled for the conversion. The maximum number of merge candidates for the coding tool is zero or a positive number.