Image Coding With Region Flags for Efficient MTS Transforms
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Solution Overview
Problem
The increasing demand for high-resolution and high-quality images/videos, particularly in immersive media formats like VR and AR, leads to higher transmission and storage costs due to increased bit amounts, necessitating a more efficient image/video compression technique.
Innovation Solution
An image coding method that includes deriving flag information to determine the presence of significant coefficients in specific regions of a block, parsing an MTS index, and applying a transform kernel to enhance coding efficiency, particularly through the use of a scan subblock approach.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution and high-quality image/video data is transmitted or stored, then image quality is improved, but transmission cost and storage cost increase
Solution Approach 1:
The transform coefficient block is divided into multiple regions (e.g., first region and second region), and different processing methods are applied to each region. Significant coefficients are identified and processed differently from non-significant coefficients, enabling more efficient compression while preserving image quality.
Solution Approach 2:
Different coding methods are applied to different regions of the transform coefficient block based on the presence of significant coefficients. Regions with significant coefficients use one coding approach while regions without significant coefficients use another approach, optimizing compression efficiency for each local area.
2Quantity of substance
If conventional compression techniques are used, then transmission cost is reduced, but image quality deteriorates
Solution Approach 1:
The coding method dynamically adapts to the characteristics of each transform coefficient block by identifying significant coefficients and adjusting the coding approach accordingly. This dynamic adaptation allows the system to maintain high image quality while achieving efficient compression.
Solution Approach 2:
The invention changes coding parameters (such as transform type, quantization step size, or coding mode) based on the distribution of significant coefficients in different regions, optimizing the balance between compression ratio and image quality for each specific case.
3Productivity
If transform coding is applied to entire block, then compression efficiency is improved, but coding complexity increases
Solution Approach 1:
The transform coefficient block is segmented into multiple regions, and different coding strategies are applied to each region. This segmentation reduces the overall coding complexity by allowing simpler methods to be used in regions without significant coefficients while maintaining compression efficiency in regions with important information.
Solution Approach 2:
Instead of applying complex coding methods to the entire block, the invention applies sophisticated coding only to regions containing significant coefficients, while using simpler methods in other regions. This partial application of complex coding reduces overall complexity while maintaining necessary compression efficiency.
Data Source
AI summary
An image decoding method according to the present document comprises the steps of: deriving flag information indicating whether valid coefficients are present in a second area excluding a first area of the upper left corner of the current block; parsing an MTS index from a bitstream on the basis of the flag information indicating the absence of valid coefficients in the second area; and deriving residual samples for the current block by applying a conversion kernel derived on the basis of the MTS index to conversion coefficients of the first area, wherein the flag information may be derived by determining, for each scan sub-block in which the valid coefficients are scanned, whether the valid coefficients are present in the second area.