Image Coding Transform Selection Based on Block Properties
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Solution Overview
Problem
The increasing demand for high-resolution and high-quality images/videos, such as 4K and 8K ultra high definition, leads to higher bit rates and increased transmission and storage costs. Additionally, the need for efficient compression techniques is exacerbated by the rise of immersive media like virtual and augmented reality.
Innovation Solution
The proposed solution involves an image coding method and apparatus that utilizes Multiple Transform Selection (MTS) and MTS index signaling to enhance coding efficiency. This method determines whether to parse an MTS index based on specific conditions, such as block size and partition type, to apply the MTS effectively and reduce unnecessary computations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution and high-quality images/videos are transmitted or stored, then image quality is improved, but transmission cost and storage cost increase
Solution Approach 1:
The patent applies parameter changes by dynamically selecting transform types (e.g., DCT, DST, ADCT) based on block characteristics and coding conditions. The transform type is determined through rate-distortion optimization, changing the transformation parameter adaptively to achieve better compression efficiency while maintaining image quality, thereby reducing the bit amount required for transmission and storage.
Solution Approach 2:
The invention implements dynamics through adaptive transform selection where the transform type is not fixed but dynamically adjusted based on block size, prediction mode, and coding context. The system dynamically determines whether to apply MTS (Multiple Transform Selection) or single transform, and which specific transform to use, optimizing the balance between compression efficiency and quality for each specific coding situation.
2Device complexity
If transform selection is simplified, then device complexity is reduced, but coding efficiency decreases
Solution Approach 1:
The patent applies segmentation by dividing the transform selection process into manageable segments based on block characteristics. Different transform types are selected for different block sizes and regions (e.g., luma vs. chroma blocks, different partition types). This segmented approach reduces the overall complexity by handling each segment with appropriate simplicity while maintaining high coding efficiency through optimized local transform selection.
Solution Approach 2:
The invention changes the selection parameter from a fixed transform type to an adaptive parameter that varies based on block size, prediction mode, and coding context. By making the transform parameter dynamic rather than static, the system achieves high coding efficiency without requiring complex transform selection logic for every possible case, as the parameter changes are driven by straightforward conditional rules.
3Adaptability or versatility
If MTS index parsing is performed for all blocks, then coding flexibility is improved, but processing time increases
Solution Approach 1:
The patent applies partial action by selectively parsing MTS index only for blocks that require it, rather than universally parsing for all blocks. The system determines whether to parse MTS index based on conditions such as block size (e.g., only for blocks with width or height greater than 32), partition type, and whether the block is divided into sub-partition blocks. This partial parsing approach maintains coding flexibility for complex blocks while avoiding unnecessary processing time for simpler blocks.
Solution Approach 2:
The invention performs preliminary determination of whether MTS index parsing is needed before actually parsing the index. By pre-evaluating block characteristics (size, partition type, sub-block status) and setting appropriate flags or decisions in advance, the system avoids time-consuming parsing operations for blocks where MTS is not applicable, thereby reducing overall processing time while preserving flexibility where needed.
4Productivity
If transform is applied to all blocks, then compression efficiency is improved, but computational complexity increases
Solution Approach 1:
The patent applies local quality by applying transforms selectively based on local block characteristics rather than uniformly to all blocks. Different transform types are applied to different blocks according to their specific properties (e.g., luma blocks vs. chroma blocks, different sizes, different partition types). This localized approach maintains high compression efficiency for blocks that benefit from transforms while avoiding unnecessary computational complexity for blocks where transforms would not provide significant benefit.
Data Source
AI summary
An image decoding method, according to the present document, comprises the steps of: determining whether to parse an MTS index for applying an MTS to the current block; deriving residual samples for the current block by applying the MTS to the current block on the basis of the MTS index; and generating a reconstructed picture on the basis of the residual samples, wherein the step of determining whether to parse the MTS index includes determining the tree type of the current block, the division type of the current block, and whether zero-out for the MTS has been performed in the current block.