Hierarchical Coding Unit Split Structure for Image Decoding
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Solution Overview
Problem
Existing image decoding methods face inefficiencies in extracting information about split structures and skip modes from images encoded using hierarchical coding units of varying sizes, which affects compression and transmission efficiency.
Innovation Solution
A method that splits a current picture into maximum coding units, determines split structures and prediction modes based on deeper coding units, and encodes and decodes split and skip information to efficiently handle hierarchical coding units, allowing for adaptive encoding and decoding processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If hierarchical coding units of various sizes are used for image encoding, then compression efficiency is improved, but the complexity of extracting split structure information and skip mode information during decoding increases
Solution Approach 1:
The image is divided into hierarchical coding units of various sizes through systematic segmentation. The picture is first divided into maximum coding units, which are then recursively divided into smaller coding units at different depths. This segmentation enables efficient compression by adapting to local image characteristics while maintaining a structured decoding process through hierarchical organization of split information.
2Manufacturing precision
If maximum coding units are divided into smaller coding units at multiple depths, then encoding precision is improved, but the amount of split information to be decoded increases
Solution Approach 1:
Different regions of the image are encoded with different precision levels by dividing maximum coding units into smaller coding units at multiple depths based on local image characteristics. This allows high-precision encoding in complex regions while using coarser encoding in simple regions, optimizing the balance between encoding precision and information overhead through adaptive local quality adjustment.
3Loss of substance
If skip mode is used for macroblocks with identical motion vectors, then bit amount is reduced, but the complexity of identifying and processing skip mode information increases
Solution Approach 1:
The decoding process leverages self-service by using previously decoded motion vector information from adjacent blocks to automatically determine skip mode status for current coding units. This eliminates the need for separate complex skip mode identification processes, as the decoder naturally identifies skip opportunities through motion correlation with neighboring blocks, reducing both bit amount and processing complexity.
Data Source
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AI summary
Methods and apparatuses for encoding and decoding an image. The method of encoding an image, the method includes: splitting a current picture into at least one maximum coding unit; determining a split structure of the at least one maximum coding unit, and a prediction mode and partitions of each coding unit by encoding image data of the at least one maximum coding unit based on deeper coding units according to depths; setting skip information and split information about split of a coding unit of an upper depth including the each coding unit, according to the each coding unit; and encoding the split information and skip information, which are set according to the each coding unit.