Adaptive Coding Distortion Removal via Block Boundary Filtering
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Solution Overview
Problem
Conventional coding distortion removal methods are complex, difficult to implement, and often degrade image quality due to high data processing rates and the inability to accurately distinguish image signals from coding distortion without additional information.
Innovation Solution
A simplified coding distortion removal method that adapts filter usage based on whether the motion compensation unit boundary matches the coding unit boundary, and whether the boundary is a motion compensation block boundary or not, with specific steps for identifying pixels and applying filtering to reduce processing and maintain image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional coding distortion removal methods are used, then coding distortion can be removed, but the processing becomes complex and image quality degrades
Solution Approach 1:
The patent segments the image into multiple blocks and processes each block independently with its own filter coefficients. This divides the complex global processing into simpler local operations, reducing overall processing complexity while maintaining distortion removal effectiveness.
Solution Approach 2:
The patent applies different filter coefficients to different blocks based on local characteristics such as block boundary strength and pixel variation. This local adaptation allows effective distortion removal in areas where it is needed while avoiding unnecessary processing in other areas, simplifying the overall system.
2Reliability
If conventional coding distortion removal methods are used, then coding distortion can be removed, but image quality degrades due to high data processing rates
Solution Approach 1:
The patent calculates different filter coefficients for each block based on local characteristics including block boundary strength and pixel variation within the block. This localized approach removes coding distortion effectively from block boundaries while preserving image quality in regions where distortion is not present, preventing the degradation that occurs with uniform high-strength filtering.
Solution Approach 2:
The patent dynamically adjusts filter coefficients based on local image characteristics such as pixel variation and block boundary strength. By changing the filtering parameters adaptively rather than applying fixed strong filtering, the system removes distortion effectively while maintaining image quality.
3Reliability
If conventional coding distortion removal methods are used, then coding distortion can be removed, but additional information is required to distinguish image signals from coding distortion
Solution Approach 1:
The patent uses only the decoded block data itself to calculate filter coefficients, examining local characteristics such as pixel variation and block boundary strength within the block. This self-service approach eliminates the need for additional reference information or complex side information, simplifying the system while maintaining effective distortion removal.
Data Source
AI summary
A coding distortion removal method for removing coding distortion in an image which was has been divided in to a plurality of macroblocks. The method operates under the following conditions such that: (i) a size of a pixel in a motion compensation block is smaller than a size of a pixel in said macroblock; (ii) a size of a pixel in a motion compensation block is larger than a size of a pixel in a coding unit; and (iii) a pixel difference between two adjacent motion compensation blocks located inside the macroblock is zero. The method disables the coding distortion removal at a boundary between blocks located inside each of the two adjacent motion compensation blocks, and enables the coding distortion removal at a boundary between the two adjacent motion compensation blocks.