Hierarchical Tree Coding Units for Video Compression
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Solution Overview
Problem
Existing video codecs face inefficiencies in encoding and decoding high-resolution video content, as they rely on fixed macroblock sizes and methods that do not adapt well to varying image characteristics, leading to decreased compression efficiency and increased data complexity.
Innovation Solution
The implementation of a video encoding and decoding method using hierarchical coding units with a tree structure, which allows for variable depth and size adjustments based on image characteristics, enabling more efficient encoding and decoding by splitting images into maximum coding units and determining coded depths for optimal encoding modes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If fixed macroblock sizes are used for encoding, then the encoding process is simple, but compression efficiency decreases for high-resolution video
Solution Approach 1:
The video picture is divided into multiple maximum coding units, which are further divided into smaller coding units according to different depths, forming a tree structure. This segmentation allows the encoder to process different regions at different levels of detail, improving compression efficiency while maintaining manageable complexity through systematic division.
Solution Approach 2:
The coding unit size is made dynamic by introducing depth-based hierarchical splitting. Instead of using fixed macroblock sizes, the system adapts the coding unit size by varying the depth of division, allowing larger coding units for smooth regions and smaller coding units for detailed regions, thereby optimizing compression efficiency.
2Productivity
If variable depth hierarchical coding units are used, then compression efficiency improves, but device complexity increases
Solution Approach 1:
The encoding process is segmented into distinct stages: dividing the picture into maximum coding units, then recursively dividing them into smaller units at different depths. This structured segmentation manages complexity by breaking down the complex task of variable-size block processing into systematic, repeatable steps.
Solution Approach 2:
The coding units are organized in a nested hierarchical structure where larger coding units contain smaller subdivided units at different depths. This nesting approach manages complexity by organizing the variable-size blocks in a regular tree structure, where each level follows the same division pattern, making the complex variable-depth structure more manageable.
3Speed
If fixed macroblock encoding is used, then processing speed is maintained, but adaptation to image characteristics is poor
Solution Approach 1:
Different regions of the video picture are processed with different coding unit sizes and depths according to their local characteristics. Smooth regions use larger coding units for faster processing, while regions with high detail or complexity use smaller coding units for better quality, achieving both speed and adaptability.
Solution Approach 2:
The coding unit size dynamically adapts to image characteristics through depth-based hierarchical division. The system can adjust the depth of division for different maximum coding units based on local image content, allowing faster processing of simple regions while maintaining high quality for complex regions.
4Quantity of substance
If hierarchical coding units with tree structure are used, then the number of macroblocks is reduced, but decoding complexity increases
Solution Approach 1:
The decoding process segments the bitstream processing according to the hierarchical tree structure of coding units. By organizing decoding operations to follow the same systematic division pattern used in encoding, the system reduces the total number of blocks that need to be processed while managing complexity through structured, level-by-level decoding.
Solution Approach 2:
The nested hierarchical structure of coding units at different depths allows the decoder to process larger units first and only decode smaller subdivided units when necessary. This nesting approach reduces the overall number of decoding operations compared to processing all fixed-size macroblocks, while the regular tree structure keeps the decoding logic manageable.
Data Source
AI summary
Provided are a method and apparatus for encoding a video and a method and apparatus for decoding a video. The encoding method includes: splitting a picture of the video into one or more maximum coding units that are coding units having a maximum size; encoding the picture based on coding units according to depths which are obtained by hierarchically splitting each of the one or more maximum coding units according to depths in each of the one or more maximum coding units, determining coding units according to coded depths with respect to each of the coding units according to depths, and thus determining coding units having a tree structure; and outputting data that is encoded based on the coding units having the tree structure, information about the coded depths and an encoding mode, and coding unit structure information indicating a size and a variable depth of a coding unit.