Leaf-Node Prediction Mode Reset for Lower-Bit Image Coding
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Solution Overview
Problem
The increasing demand for high-resolution and high-quality images leads to a significant increase in transmission and storage costs due to the increased amount of information, necessitating more efficient image compression technologies.
Innovation Solution
An image encoding/decoding method that resets the prediction mode type based on the slice type or size of a current block, allowing for improved encoding/decoding efficiency by optimizing prediction mode information transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution and high-quality image data is transmitted, then image quality is improved, but transmission cost and storage cost increase
Solution Approach 1:
The patent changes the parameter of prediction mode signaling by resetting the prediction mode type based on slice type and block size. This parameter change enables more efficient compression of prediction mode information, reducing the number of bits required to encode high-resolution images while maintaining image quality. The conditional resetting of prediction modes based on slice and block characteristics optimizes the balance between compression efficiency and reconstruction quality.
2Manufacturing precision
If prediction mode information is transmitted for each block, then encoding precision is improved, but data transmission volume increases
Solution Approach 1:
The patent applies local quality by differentiating prediction mode signaling based on local characteristics of image blocks. Specifically, prediction mode type is reset conditionally based on slice type and block size, meaning that different regions of the image use different prediction mode signaling strategies. This local adaptation maintains high encoding precision where needed while reducing data transmission volume in regions where simpler prediction modes suffice.
Solution Approach 2:
The patent segments the image processing into slices and blocks, applying different prediction mode reset rules to different segments. By dividing the image into manageable units (slices and blocks) and applying conditional prediction mode resetting at each segment level, the patent achieves efficient compression while maintaining encoding precision. This segmentation allows the system to adapt prediction mode signaling to local image characteristics without processing the entire image uniformly.
Data Source
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AI summary
An image encoding/decoding method and apparatus are provided. An image decoding method performed by an image decoding apparatus comprises obtaining a current block corresponding to a leaf node of a split tree structure based on a predetermined prediction mode type, resetting a prediction mode type of the current block, obtaining prediction mode information of the current block based on the reset prediction mode type, and generating a prediction block of the current block based on the prediction mode information. The resetting the prediction mode type of the current block may be performed based on at least one of a slice type or size of the current block.