Chroma Deblocking Boundary Strength for Joint CbCr Coding
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Solution Overview
Problem
The increasing demand for high-resolution and high-quality images leads to an increase in transmission and storage costs due to the rise in the amount of transmitted information, necessitating high-efficient image compression technology.
Innovation Solution
An image encoding/decoding method and apparatus that determines boundary strength for deblocking filtering, utilizing joint CbCr residual coding and flags to enhance encoding/decoding efficiency, and transmits a bitstream generated by this process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If high-resolution and high-quality images are transmitted, then image quality is improved, but transmission cost and storage cost increase
Solution Approach 1:
The patent changes the parameter of boundary strength values (0, 1, or 2) to control the intensity of deblocking filtering. By adjusting this parameter based on transform coefficient characteristics, the system optimizes image quality while reducing unnecessary filtering operations, thereby lowering processing costs and improving efficiency without sacrificing quality.
Solution Approach 2:
The patent applies different boundary strength values to different boundaries within the image based on local characteristics. Boundaries with higher boundary strength values receive stronger filtering, while boundaries with lower values receive weaker or no filtering. This local differentiation allows the system to maintain high quality in critical areas while reducing processing overhead in less critical areas.
2Manufacturing precision
If deblocking filtering is applied to all boundaries, then image quality is improved, but processing time and computational complexity increase
Solution Approach 1:
The patent evaluates local characteristics of transform coefficients at each boundary to determine the appropriate boundary strength value. By making filtering strength adaptive to local content characteristics, the system applies strong filtering only where needed (at boundaries with high boundary strength values) and uses weak or no filtering where content characteristics indicate it is unnecessary, thereby reducing overall processing time while maintaining quality.
Solution Approach 2:
The patent dynamically adjusts the boundary strength values based on the characteristics of transform coefficients at each boundary. The boundary strength is not fixed but is calculated in real-time based on the specific content at each boundary, allowing the filtering process to adapt its intensity to the actual needs of the image data, thus optimizing the balance between quality improvement and processing efficiency.
3Device complexity
If uniform boundary strength values are used for all boundaries, then processing is simplified, but image quality deteriorates due to over-filtering or under-filtering
Solution Approach 1:
The patent calculates boundary strength values (0, 1, or 2) based on the local characteristics of transform coefficients at each boundary. This local adaptation ensures that each boundary receives the appropriate filtering strength: strong filtering (boundary strength value of 2) for boundaries with high-frequency content, moderate filtering (boundary strength value of 1) for intermediate cases, and weak or no filtering (boundary strength value of 0) for boundaries where the transform coefficients indicate smooth transitions or flat regions, thereby avoiding both over-filtering and under-filtering while maintaining image quality.
Solution Approach 2:
The patent changes the boundary strength parameter dynamically based on transform coefficient characteristics. Instead of using a fixed uniform boundary strength value, the system calculates and applies different boundary strength values (0, 1, or 2) for different boundaries within the same image, allowing the filtering process to adapt its intensity to the specific content characteristics at each boundary, thus optimizing image quality while managing processing complexity through systematic evaluation criteria.
Data Source
AI summary
An image encoding/decoding method and apparatus are provided. An image decoding method according to the present disclosure may comprise obtaining a reconstructed picture, determining a target boundary of deblocking filtering in the reconstructed picture, determining a boundary strength for the target boundary, and applying deblocking filtering to the target boundary based on the boundary strength. Based on the target boundary being a transform block boundary and a color component of the reconstructed picture being a chroma component, the boundary strength may be determined based on whether joint CbCr residual coding is performed on at least one of two blocks adjacent to the target boundary, and the joint CbCr residual coding may correspond to encoding residual samples for a chroma Cb component and a chroma Cr component as a single transform block.