Adaptive Transform Image Encoding Block Splitting
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Solution Overview
Problem
The increasing demand for high-resolution and high-quality images leads to a significant increase in the amount of transmitted and stored data, resulting in higher costs and the need for more efficient image compression technologies.
Innovation Solution
An image encoding/decoding method and apparatus that performs adaptive transform, determining a current block by splitting an image based on split information from a bitstream, and calculating a quantization parameter to optimize transform coefficients within a predetermined range, thereby improving encoding/decoding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If image resolution and quality are improved, then image quality is improved, but the amount of transmitted information increases
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the transform type (e.g., DCT, DST, KLT) and transform block size based on the characteristics of the current block. This adaptive approach optimizes the compression efficiency for different image regions, allowing high-quality reconstruction with fewer bits by matching the transform parameters to the local image content statistics.
Solution Approach 2:
The patent introduces dynamic adaptability through the adaptive transform selection mechanism. The encoder dynamically determines the optimal transform type and block size for each current block based on residual energy, block size, and other characteristics. This dynamic parameter adjustment enables efficient compression across varying image content while maintaining high quality.
2Manufacturing precision
If image resolution and quality are improved, then image quality is improved, but transmission cost increases
Solution Approach 1:
By changing transform parameters adaptively based on block characteristics, the patent achieves better energy compaction and sparsity in the transform domain. This leads to more efficient entropy coding and reduced bitrate requirements, thereby lowering transmission costs while preserving image quality.
Solution Approach 2:
The patent applies different transform types and parameters to different regions (current blocks) based on their local characteristics. This local optimization ensures that each region is encoded with the most efficient parameters, reducing overall transmission energy while maintaining quality across the entire image.
3Manufacturing precision
If image resolution and quality are improved, then image quality is improved, but storage cost increases
Solution Approach 1:
The adaptive transform parameter selection optimizes the compression ratio by achieving better energy compaction. This results in smaller encoded file sizes for the same image quality, directly reducing storage costs while maintaining high-resolution and high-quality image reconstruction.
4Productivity
If adaptive transform is performed, then encoding efficiency is improved, but device complexity increases
Solution Approach 1:
The patent segments the image into current blocks and applies transform selection at the block level. This segmentation allows the complexity to be distributed and managed at a fine granularity, where simple rules or lookup tables can determine the transform type for each block, keeping the overall system complexity manageable while achieving high encoding efficiency.
Solution Approach 2:
The patent implements adaptive transform selection, which adds some complexity, but applies it selectively based on block characteristics. The transform selection mechanism is triggered only when beneficial, and uses simple criteria (residual energy, block size) to make decisions, thereby achieving improved encoding efficiency without excessive complexity increase.
Data Source
AI summary
An image encoding/decoding method and apparatus are provided. The image decoding method performed by the image decoding apparatus, according to the present disclosure, comprises the steps of determining a current block by splitting an image on the basis of split information acquired from a bitstream; determining a quantization parameter of the current block; and determining a transform coefficient of the current block on the basis of the quantization parameter.