Asymmetric Deblocking Filter for Low-Complexity Video Coding
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Solution Overview
Problem
Existing video coding technologies suffer from visible edge artifacts due to block-based coding, necessitating improved deblocking filters to enhance picture quality without increasing computational complexity.
Innovation Solution
A deblocking filter apparatus and method that utilizes an asymmetric filter to modify sample values on either side of a block edge, adjusting the number of modified samples based on available line buffer size to optimize filtering decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional deblocking filtering is applied to remove edge artifacts, then picture quality is improved, but computational complexity increases
Solution Approach 1:
The patent applies different filtering strengths to different regions: strong filtering at CTB boundaries where artifacts are most visible, and reduced or no filtering in other areas. This localized approach maintains picture quality where needed while reducing overall computational complexity
Solution Approach 2:
The filtering process is segmented into different regions based on CTB boundaries. The deblocking filter is applied selectively to blocks adjacent to CTB boundaries rather than uniformly across the entire picture, dividing the processing into manageable segments that reduce total computational load
2Productivity
If asymmetric filtering is applied to optimize filtering decisions based on line buffer size, then filtering efficiency is improved, but device complexity increases
Solution Approach 1:
The filtering parameters (tap length, filtering strength) are dynamically adjusted based on the available line buffer size and the specific location relative to CTB boundaries. This dynamic adaptation optimizes filtering efficiency for different hardware configurations without requiring multiple fixed filtering paths
Solution Approach 2:
The patent changes filtering parameters (number of taps, filtering strength) based on the line buffer size and CTB boundary conditions. By adjusting these parameters dynamically, the system achieves optimal filtering efficiency for different hardware capabilities while managing device complexity through parameter adaptation rather than structural complexity
Data Source
AI summary
A method and image processing device are provided, including a deblocking filter. The deblocking filter modifies values of at most MA samples of the first image block as first filter output values, the at most MA samples being located at a column of the first image block that is perpendicular to and adjacent to the horizontal block edge; and modifies values of at most MB samples of the second image block as second filter output values, the at most MB samples being located at a column of the second image block that is perpendicular to and adjacent to the horizontal block edge. At most a number MA of sample values of the first image block adjacent to the block edge are modified and at most a number MB of sample values of the second image block adjacent to the block edge are modified, wherein MA<MB.