Adaptive Tile Structure for Video Coding Efficiency
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Solution Overview
Problem
The increasing demand for high-resolution and high-quality pictures, such as HD and UHD, leads to higher data amounts, resulting in increased transmission and storage costs. Existing video compression techniques struggle to efficiently adapt to the varying data requirements across different parts of an image.
Innovation Solution
The method involves configuring a tile structure with various types of structures by splitting the current picture into at least two tiles using column splitting and row splitting, where the splitting lengths can be shorter than the picture's height or width. This approach allows for adaptive coding by determining the column and row splitting based on various information parameters, such as tile number, size, and position, and by configuring slices within tiles with different boundary directions and adaptive scan orders.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the current picture is split into multiple tiles with fixed splitting lengths equal to picture height or width, then the tile structure is simple and easy to implement, but the coding efficiency cannot be adapted to different data requirements of various image regions
Solution Approach 1:
The current picture is divided into multiple tiles through column splitting and row splitting, where each tile can be independently coded. The splitting lengths are configured to be shorter than the full picture height or width, creating multiple smaller tile regions that can be adaptively managed based on local data requirements
Solution Approach 2:
The tile structure employs dynamic configuration where the number of column splits and row splits can be adjusted based on picture characteristics. The split information is encoded using variable-length coding, allowing the tile structure to adapt dynamically to different content requirements while maintaining flexibility in coding efficiency
2Reliability
If high-resolution and high-quality picture data is transmitted or stored using conventional methods, then the image quality is maintained, but the transmission cost and storage cost increase due to the large amount of data
Solution Approach 1:
By dividing the picture into multiple tiles that can be independently coded and transmitted, the system enables selective compression and prioritization of different regions. This segmentation allows high-quality transmission of important regions while applying higher compression to less critical areas, reducing overall transmission and storage costs while maintaining perceived image quality
Solution Approach 2:
The tile structure enables different coding parameters and quality levels to be applied to different regions of the picture. Each tile can be encoded with appropriate quality settings based on its content importance, allowing the system to maintain high quality where needed while reducing data量 in less critical areas, thereby lowering transmission and storage costs
Data Source
AI summary
The present invention discloses a method for constructing a tile structure, wherein a current picture includes at least two or more tiles, the at least two or more tiles are split by a column splitting and a row splitting, at least one or more of the column splitting and the row splitting are performed by using a splitting length which is shorter than a width length or a height length of the current picture.