Hierarchical Video Coding Unit Scanning Order Optimization
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Solution Overview
Problem
Existing video codecs struggle with efficiently encoding and decoding high-resolution video content due to limitations in encoding methods based on fixed macroblock sizes, leading to decreased data compression efficiency and increased complexity.
Innovation Solution
The proposed solution involves a video encoding and decoding method based on a hierarchical structure, where pictures are split into maximum coding units and further divided into coding units with varying depths, allowing for adaptive scanning orders based on absolute and relative locations, optimizing encoding and decoding processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a video is encoded according to a limited encoding method based on a macroblock having a predetermined size, then the encoding process is simple, but the data compression efficiency decreases and complexity increases for high-resolution video content
Solution Approach 1:
The picture is divided into multiple maximum coding units, and each maximum coding unit is further divided into coding units of different depths. This hierarchical segmentation allows the encoding process to handle high-resolution video more efficiently by working with smaller, manageable units while maintaining overall compression effectiveness
Solution Approach 2:
The patent introduces a depth dimension to the traditional two-dimensional macroblock structure by creating a hierarchical tree structure with multiple levels (depths). This adds a third dimension to the encoding approach, allowing for more flexible and efficient compression of high-resolution content
2Ease of operation
If a video is encoded according to a limited encoding method based on a macroblock having a predetermined size, then the encoding process is straightforward, but the complexity increases for high-resolution video content
Solution Approach 1:
By segmenting the picture into maximum coding units and further into coding units of different depths, the system manages complexity through hierarchical organization. This allows the encoder to process high-resolution video in a structured manner, reducing operational complexity while maintaining compression efficiency
Solution Approach 2:
The patent introduces dynamic elements by allowing different scanning orders (raster, diagonal, zigzag) based on the characteristics of different coding units. This dynamic adaptation enables the encoding process to optimize for each region independently, managing overall system complexity while improving performance
3Adaptability or versatility
If fixed macroblock sizes are used for encoding, then the encoding method is limited and simple, but it leads to decreased data compression efficiency
Solution Approach 1:
The patent makes the encoding method dynamic by introducing multiple scanning orders (raster, diagonal, zigzag) that can be selected based on the characteristics of each coding unit. This adaptability allows the encoder to optimize compression efficiency for different types of video content and regions within the picture
Solution Approach 2:
The patent changes key parameters including coding unit size, depth levels, and scanning order to optimize compression efficiency. By varying these parameters based on picture characteristics, the encoding method becomes more adaptable and achieves better compression results for high-resolution video content
Data Source
AI summary
A video decoding method and apparatus and a video encoding method and apparatus based on a scanning order of hierarchical data units are provided. The decoding method includes: receiving and parsing a bitstream of an encoded video; extracting from the bitstream information about a size of a maximum coding unit for decoding a picture of the encoded video, and encoding information about a coded depth and an encoding mode for coding units of the picture, wherein the size of the maximum coding unit is a maximum size of a coding unit which is a data unit for decoding the picture; and determining a hierarchical structure of the maximum coding unit and the coding units into which the picture is divided according to depths, and decoding the picture based on the coding units, by using the information about the size of the maximum coding unit and the encoding information about the coded depth and the encoded mode.