Adaptive Image Block Division for Video Encoding Prediction Accuracy
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing video encoding and decoding technologies lack flexibility in image block division, resulting in suboptimal prediction accuracy and encoding/decoding performance.
Innovation Solution
The proposed method allows for multiple image block division manners, including square and non-square divisions, with horizontal and vertical directions, enabling better prediction accuracy by dividing image blocks into rectangular subblocks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If square division is used for image blocks, then the encoding process is simple, but prediction accuracy is insufficient
Solution Approach 1:
The patent divides image blocks into multiple subblocks using different division manners (square, horizontal, vertical, diagonal). This segmentation allows the encoding system to adapt to different image content characteristics, improving prediction accuracy while maintaining encoding efficiency through selective application of division types.
Solution Approach 2:
The patent introduces dynamic selection of division manners based on image content analysis. The encoding apparatus adaptively chooses between square, horizontal, vertical, and diagonal division methods according to the specific characteristics of each image block, transforming the static square division into a dynamic, content-adaptive process that improves prediction accuracy.
2Measurement precision
If multiple image block division manners are introduced, then prediction accuracy is improved, but device complexity increases
Solution Approach 1:
The patent applies different division manners to different regions of the image based on local characteristics. By analyzing image content and selecting appropriate division types (square, horizontal, vertical, diagonal) for specific blocks, the system improves prediction accuracy locally without requiring complex processing for the entire image, thus balancing complexity and performance.
Solution Approach 2:
The patent changes the division parameters (division manner, direction, and granularity) based on image content analysis. By dynamically adjusting these parameters, the system achieves high prediction accuracy without requiring fundamentally complex encoding architecture, as the complexity is managed through parameter selection rather than structural complexity.
3Productivity
If traditional square division is used, then encoding efficiency is maintained, but encoding and decoding effects are suboptimal
Solution Approach 1:
The patent transforms the static square division approach into a dynamic system that selects from multiple division manners (square, horizontal, vertical, diagonal) based on image content. This dynamic adaptation improves encoding and decoding effects by matching the division strategy to the actual image characteristics while maintaining efficient encoding through automated selection.
Solution Approach 2:
The patent optimizes encoding effects by changing division parameters (manner, direction, granularity) based on image content analysis. This parameter adaptation allows the system to achieve better compression ratios and reconstruction quality without sacrificing encoding efficiency, as the parameter selection is automated and integrated into the encoding pipeline.
Data Source
AI summary
An decoding method is disclosed, including: parsing a received bitstream to determine whether a current image block is required to be partitioned; parsing the bitstream to determine a partition direction when the current image block is required to be partitioned, wherein the partition direction is a horizontal direction; partitioning the current image block into four rectangular subblocks when the partition direction is the horizontal direction, wherein a size of the current image block is expressed as 16×H, with H representing a height of the current image block and 16 is a width of the current image block, wherein H is not equal to 16, and wherein a size of each of the four rectangular subblocks is expressed as 16×H/4; and reconstructing the current image block based on the four rectangular subblocks.