QTBT Image Deblocking for Parallel Video Decoding
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Solution Overview
Problem
Existing de-blocking filters for video encoding, such as those used in HEVC, are inefficient when applied to the quad-tree plus binary-tree (QTBT) structure, leading to issues with parallel processing and subjective/objective image quality degradation due to inconsistent filtering conditions across block boundaries.
Innovation Solution
Adaptive de-blocking filtering is applied based on block size, where filtering is performed only on block boundaries with dimensions of 8 or larger, and specific conditions are met for smaller blocks, ensuring parallel implementation and maintaining image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If de-blocking filtering is applied to all block boundaries in QTBT structure, then image quality is improved, but processing complexity and time increase
Solution Approach 1:
The patent applies different de-blocking filtering strategies to different block boundaries based on their specific characteristics. Small blocks (width or height ≤ 4) use different filtering conditions compared to large blocks, allowing optimized processing for each local region rather than uniform processing across the entire image.
Solution Approach 2:
The filtering conditions are dynamically adjusted based on block dimensions. The patent introduces dynamic threshold values (β and tc) that vary depending on whether the block is small (≤4) or large (>4), enabling adaptive filtering strength for each block type to balance quality and processing efficiency.
2Manufacturing precision
If de-blocking filtering is applied to small blocks (width or height ≤ 4), then image quality is improved, but parallel processing efficiency decreases
Solution Approach 1:
The patent treats small blocks (width or height ≤ 4) differently from large blocks in terms of filtering conditions. Small blocks use specific reference pixel determination methods and filtering thresholds that are optimized for their size, allowing quality improvement without forcing the same processing requirements on all block types.
3Manufacturing precision
If filtering conditions are made more strict for small blocks, then image quality is improved, but the number of blocks requiring processing increases
Solution Approach 1:
The patent applies different filtering criteria to small blocks versus large blocks. Small blocks (width or height ≤ 4) have specific filtering conditions that may be more restrictive, while large blocks use different conditions, thereby optimizing the balance between quality improvement and processing complexity for each local region.
Solution Approach 2:
The patent changes filtering parameters (such as boundary strength thresholds and reference pixel selection) based on block size. By adjusting these parameters dynamically according to whether a block is small (≤4) or large (>4), the system optimizes processing complexity for each block type while maintaining overall image quality.
Data Source
AI summary
The present invention discloses an image coding/decoding method and an apparatus for the method. More specifically, a method for filtering an image by a decoding apparatus comprises deriving boundaries of a block divided into quad-tree plus binary-tree structure; determining an edge among boundaries of the block to which de-blocking filtering is applied; determining a type of de-blocking filtering to be applied to the edge; and performing de-blocking filtering to a picture sample restored according to the de-blocking filtering type, wherein the edge or the type of de-blocking filtering is determined by considering width or height of the block.