Image Encoding Block Splitting Based on Color Format Prediction
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Solution Overview
Problem
Current image encoding and decoding technologies face inefficiencies in handling high-resolution and high-quality images, leading to increased transmission and storage costs due to the large amount of data required.
Innovation Solution
An image encoding and decoding method that determines a splitting mode based on the color format, allowing for efficient encoding and decoding by splitting blocks into dual tree structures and independently determining the splitting availability of luma and chroma blocks, optimizing bitstream transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If image resolution and quality are improved, then image quality is enhanced, but transmission cost and storage cost increase
Solution Approach 1:
The image is divided into multiple blocks that are processed independently. The current block is split into lower-layer blocks, and different prediction mode types (intra, inter, skip) are applied to different blocks based on their characteristics. This segmentation allows for more efficient compression while maintaining overall image quality.
Solution Approach 2:
Different prediction mode types are selectively applied to different blocks within the image based on local characteristics. Intra prediction mode is used for blocks with spatial correlation, inter prediction mode for blocks with temporal correlation, and skip mode for blocks that can be reconstructed from neighboring blocks. This local optimization improves compression efficiency while preserving image quality.
2Productivity
If encoding complexity is reduced, then encoding speed increases, but decoding efficiency may deteriorate
Solution Approach 1:
The prediction mode type is determined in advance for each block based on encoding information, and this information is stored and used during decoding. By pre-determining the prediction mode types (intra, inter, skip) for lower-layer blocks, the decoding process can proceed efficiently without complex real-time analysis, thus maintaining both encoding speed and decoding efficiency.
3Ease of operation
If block splitting is performed uniformly, then processing simplicity is maintained, but encoding efficiency decreases
Solution Approach 1:
The image is divided into multiple blocks that are processed independently. The current block is split into lower-layer blocks, and different prediction mode types (intra, inter, skip) are applied to different blocks based on their characteristics. This segmentation allows for more efficient compression while maintaining overall image quality.
Solution Approach 2:
Different prediction mode types are selectively applied to different blocks within the image based on local characteristics. Intra prediction mode is used for blocks with spatial correlation, inter prediction mode for blocks with temporal correlation, and skip mode for blocks that can be reconstructed from neighboring blocks. This local optimization improves compression efficiency while preserving image quality.
Data Source
AI summary
An image encoding/decoding method and apparatus are provided. An image decoding method performed by an image decoding apparatus may comprise obtaining a current block by splitting an image, determining prediction mode characteristic information based on encoding information of the current block, determining a prediction mode type of a lower-layer block split from the current block based on the prediction mode characteristic information, obtaining the lower-layer block by splitting the current block, and decoding the lower-layer block based on the determined prediction mode type of the lower-layer block. The prediction mode characteristic information may be determined based on a color format of the current block.