Adaptive Scaling Factor for Non-Power-of-2 Image Blocks
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Solution Overview
Problem
Current video coding schemes, such as HEVC, are limited in their ability to efficiently decode and encode images due to their reliance on square block sizes for quantization and scaling, which do not adapt well to non-power-of-2 block dimensions, affecting compression efficiency and image reconstruction.
Innovation Solution
A method and device for image encoding and decoding that dynamically adjust scaling factors based on whether the block dimensions are powers of 2, allowing for proportional scaling factors to ensure accurate transformation and de-transformation of image blocks, even when block sizes are not powers of 2, thereby preserving the norm of residual blocks across domains.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If square block sizes (power of 2) are used for quantization and scaling, then the decoding and encoding process is simplified and more efficient, but the method cannot adapt to non-power-of-2 block dimensions, reducing compression efficiency and image quality
Solution Approach 1:
The patent applies dynamics by making the scaling factor adaptive rather than fixed. The scaling factor dynamically adjusts based on the actual block dimensions, allowing the system to efficiently handle both power-of-2 and non-power-of-2 block sizes. This is achieved by calculating the scaling factor as a function of the block width and height, enabling the quantization and scaling processes to adapt to varying block dimensions while maintaining computational efficiency.
2Power
If fixed scaling factors are used for power-of-2 blocks, then the transformation process is computationally efficient, but image reconstruction accuracy deteriorates when applied to non-power-of-2 blocks
Solution Approach 1:
The patent applies parameter changes by modifying the scaling factor parameter based on block dimensions. Instead of using a fixed scaling factor for all blocks, the scaling factor is recalculated as a function of the specific block width and height. This allows the system to maintain computational efficiency while improving image reconstruction accuracy for non-power-of-2 blocks by using dimension-appropriate scaling factors.
3Device complexity
If uniform quantization and scaling are applied to all block sizes, then the encoding process is simpler and faster, but compression efficiency and image quality are reduced for non-standard block sizes
Solution Approach 1:
The patent applies local quality by making the quantization and scaling parameters specific to each block's dimensions rather than uniform across all blocks. The scaling factor is locally adapted to match the actual block width and height, ensuring optimal processing for each block regardless of its size. This approach maintains relatively simple encoding while significantly improving compression efficiency and image quality for non-standard block sizes.
Data Source
AI summary
A decoding method is disclosed that comprises: —decoding a block of transform coefficients from a bitstream; —de-quantizing the decoded block of transform coefficients by a quantization step size; —scaling said dequantized block by a scaling factor; and —transforming said scaled block into an image block, wherein the scaling factor's value depends on whether at least one of the width and the height of the block is a power of 2.