Dynamic Boundary Strength Determination for Block-Based Image Deblocking
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Solution Overview
Problem
Existing block-based digital image encoding technologies, such as H.264, face inefficiencies in determining boundary strengths for deblocking processes, leading to visual defects due to incomplete recovery of original image data at edges between blocks, which affects encoding and decoding performance.
Innovation Solution
A method to determine boundary strengths of edges in a block-based digitally encoded image by considering the encoding mode and other encoding data, such as prediction residuals and motion vectors, to apply different deblocking strengths to left, top, and internal edges within macroblocks, optimizing the deblocking process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If block-based encoding is used to compress images, then encoding efficiency is improved, but visual defects appear at block edges due to incomplete recovery of original image data
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the deblocking filter strength based on boundary characteristics. Different boundary strength values (0-4) are assigned to different edges based on prediction residual sums and block types, transforming a static filtering approach into a dynamic one that adapts to local image characteristics, thereby reducing visual defects while maintaining encoding efficiency
2Object-affected harmful factors
If deblocking process is applied to all edges, then visual defects are reduced, but processing complexity and time increase
Solution Approach 1:
The patent implements local quality by applying different deblocking strengths to different edges based on their specific characteristics. Internal edges, left edges, and top edges are evaluated separately with different boundary strength determination rules. This localized approach ensures that filtering is applied appropriately only where needed, reducing overall processing complexity while effectively addressing visual defects
3Measurement precision
If boundary strength is determined using detailed encoding data analysis, then deblocking accuracy is improved, but computational overhead increases
Solution Approach 1:
The patent applies partial action by selectively analyzing encoding data based on block type and edge position. For example, Intra prediction blocks use different boundary strength rules compared to Inter prediction blocks. Motion compensation blocks have simplified evaluation. This selective analysis achieves sufficient deblocking accuracy without requiring exhaustive analysis of all encoding data, thereby reducing computational overhead
Data Source
AI summary
A method for determining the boundary strengths of edges in a block-based digitally encoded image is disclosed. The method includes setting the boundary strength of two adjacent blocks in an Inter macroblock to a first strength value if any one of the two adjacent blocks contains non-zero prediction residual in the encoding data and setting the boundary strength thereof to a second strength value if the two adjacent blocks are located in the same motion compensation block. An edge with boundary strength equal to the second strength value will be skipped in a deblocking process.