Picture Partitioning Coding for Video Compression Efficiency
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Solution Overview
Problem
The increasing demand for high-resolution, high-quality images and videos, particularly in fields like virtual reality and ultra-high definition, necessitates a highly efficient compression technique to reduce transmission and storage costs, as existing methods are inefficient in handling the increased data requirements.
Innovation Solution
A picture partitioning-based coding method and apparatus that derive a partitioning structure for images based on signaled information, including the number and dimensions of parsing columns and rows, to improve compression efficiency by determining the width and height of skip tiles relative to the last parsed values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution, high-quality images and videos are transmitted, then image quality and resolution are improved, but transmission and storage costs increase
Solution Approach 1:
The patent divides an image into multiple tiles, where each tile can be independently processed and coded. This segmentation allows the system to transmit only the essential information for each tile, reducing the overall data volume while maintaining image quality. The partitioning structure enables selective transmission of tile information based on importance and quality requirements.
Solution Approach 2:
The patent introduces partitioning parameters including the number of width parsing columns, number of height parsing rows, and skip tile indicators. These parameters control how the image is divided and coded, allowing optimization of the balance between image quality and data transmission volume. By adjusting these parameters, the system achieves efficient compression without sacrificing quality.
2Manufacturing precision
If detailed partition information is signaled for each tile, then coding precision is improved, but signaling overhead increases
Solution Approach 1:
Instead of signaling complete partition information for all tiles, the patent uses a selective approach where only certain tiles require explicit partition signaling. The skip tile indicator mechanism allows the system to infer partition information for skipped tiles based on surrounding tiles, reducing signaling overhead while maintaining sufficient coding precision for most regions.
Solution Approach 2:
The partitioning system uses contextual information from already-specified tiles to automatically determine partition parameters for skipped tiles. This self-service mechanism eliminates the need for explicit signaling of all partition details, reducing overhead while maintaining consistency in the partitioning structure across the image.
3Productivity
If more tiles are created to improve compression, then compression efficiency is improved, but parsing complexity increases
Solution Approach 1:
The patent implements a systematic parsing approach where tiles are processed in a regular sequence based on width parsing columns and height parsing rows. This periodic parsing pattern allows the system to efficiently iterate through tiles and apply compression algorithms consistently, improving compression efficiency while maintaining manageable parsing complexity through structured processing.
Data Source
AI summary
An image decoding method performed by a decoding device according to the present disclosure comprises the steps of: receiving a bitstream containing at least one of segmentation information of a current picture and prediction information for a current block included in the current picture; deriving a first segmentation structure of the current picture, which is based on multiple tiles, on the basis of the segmentation information of the current picture including at least one of information of the number of width-parsing columns, information of the last width, information of the number of height-parsing rows, and information of the last height; deriving a block predicted for the current block, on the basis of the prediction information for the current block contained in one of the multiple tiles; and generating reconstruction samples for the current block on the basis of the predicted block.