Video Coding Entry Point Signaling for Tile-Based Parallel Processing
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Solution Overview
Problem
The increasing demand for high-resolution, high-quality images/videos, particularly in fields like virtual reality and ultra-high definition, necessitates a highly efficient image/video compression technique to reduce transmission and storage costs, as existing methods are inefficient in handling high-resolution data.
Innovation Solution
The implementation of a method and apparatus that utilize Wavefront Parallel Processing (WPP) and tile technology, along with signaling entry point-related information through higher-level syntax, to enhance image coding efficiency, particularly by partitioning pictures into slices and tiles, and initializing CABAC context models for efficient encoding and decoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high resolution and high quality image/video are used, then image quality is improved, but transmission and storage costs increase
Solution Approach 1:
The picture is divided into multiple tiles, and each tile is further divided into coding tree units (CTUs). This segmentation allows for parallel processing and more efficient compression by enabling independent encoding of different regions, thereby reducing the overall transmission and storage requirements while maintaining high image quality.
2Quantity of substance
If conventional compression techniques are used, then transmission costs are reduced, but compression efficiency is insufficient for high resolution data
Solution Approach 1:
CABAC context models are initialized at the beginning of each tile and at entry points within tiles. This preliminary initialization prepares the entropy decoding process in advance, allowing for more efficient compression of high resolution data by optimizing the decoding context before actual compression occurs, thereby improving compression efficiency while reducing transmission costs.
3Productivity
If WPP and tile technology are implemented, then coding efficiency is improved, but device complexity increases
Solution Approach 1:
The implementation divides the picture into tiles and further into CTUs, creating a hierarchical structure that enables parallel processing. While this segmentation increases structural complexity, it improves coding efficiency by allowing independent processing of different regions. The complexity is managed through systematic organization and entry point management.
Solution Approach 2:
Context models are pre-initialized at tile boundaries and entry points, which prepares the decoding process in advance. This preliminary action reduces the computational burden during actual decoding, offsetting the increased device complexity by optimizing the processing workflow and improving overall coding efficiency.
4Productivity
If entry point related information is signaled through higher level syntax, then decoding efficiency is improved, but data structure complexity increases
Solution Approach 1:
Entry point information is signaled in advance through higher level syntax structures, allowing the decoder to prepare and initialize context models at the appropriate locations before actual decoding occurs. This preliminary signaling improves decoding efficiency by avoiding delays during the decoding process, while the structured approach to signaling manages the data structure complexity systematically.
Data Source
AI summary
An image decoding method according to the present document comprises the steps of: acquiring image information through a bitstream, the image information including entry point-related information; deriving at least one entry point in the current picture on the basis of the entry point-related information; and decoding the current picture on the basis of the at least one entry point, wherein the entry point-related information includes an entry point offset presence flag, offset length information, and entry point offset information, the entry point offset presence flag being related to at least one of the number of tiles in the current picture or the number of tile columns in the current picture. Through this method, the amount of data required to be signaled for video/image coding can be reduced, and coding efficiency can be increased.