3D Point Cloud Decoding with Depth-Adaptive Prediction Switching
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Solution Overview
Problem
Existing encoding methods for three-dimensional data, such as point cloud data, face challenges in achieving efficient compression and transmission due to the massive amount of data involved, necessitating improved encoding efficiency.
Innovation Solution
A decoding method and device that prioritize inter prediction for shallow nodes, use a prediction scheme indicated in control information for nodes between threshold values, and employ intra prediction for deep nodes, thereby adapting the prediction process to the depth of the current node to enhance coding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a single prediction scheme is used for all nodes, then the encoding process is simple, but encoding efficiency is insufficient for three-dimensional data with varying depth characteristics
Solution Approach 1:
The encoding process is segmented into three distinct prediction processes based on node depth thresholds. First prediction process applies to nodes with depth less than first threshold, second prediction process applies to nodes with depth between first and second thresholds, and third prediction process applies to nodes with depth greater than second threshold. This segmentation allows different prediction schemes to be applied to different regions of the three-dimensional data, improving overall encoding efficiency while maintaining manageable complexity through systematic organization.
Solution Approach 2:
The prediction scheme is made dynamic by adapting it to the depth characteristics of each node. The encoding device determines the depth of the current node and dynamically selects the appropriate prediction process (first, second, or third) based on whether the depth is less than the first threshold, between the thresholds, or greater than the second threshold. This dynamic adaptation allows the system to optimize encoding efficiency for each specific node while maintaining a structured approach to complexity management.
2Quantity of substance
If inter prediction is used for all nodes, then processing is simplified, but compression efficiency deteriorates for deep nodes where intra prediction would be more effective
Solution Approach 1:
Different prediction schemes are applied to different regions of the three-dimensional data based on their local characteristics (node depth). Shallow nodes (depth less than first threshold) use the first prediction process, intermediate nodes (depth between thresholds) use the second prediction process, and deep nodes (depth greater than second threshold) use the third prediction process. This local quality approach ensures that each node is encoded using the most appropriate prediction scheme for its specific depth characteristics, maximizing compression efficiency without requiring complex global optimization.
3Quantity of substance
If intra prediction is used for all nodes, then compression efficiency improves for deep nodes, but overall encoding efficiency deteriorates due to poor performance on shallow nodes
Solution Approach 1:
The prediction approach is changed by varying the parameter of node depth. By comparing the depth of each node against predefined thresholds (first threshold and second threshold), the system selects different prediction processes optimized for different depth ranges. This parameter-based differentiation allows the system to achieve high compression efficiency for deep nodes using intra prediction while maintaining overall encoding efficiency through appropriate selection of prediction processes for shallow and intermediate nodes.
Data Source
AI summary
A decoding method includes: in a first prediction process performed when a depth of a current node that stores a three-dimensional point is less than a first threshold value, prioritizing inter prediction over intra prediction; in a second prediction process performed when the depth is less than a second threshold value and greater than the first threshold value, using a prediction scheme indicated in control information included in a bitstream, the second threshold value being greater than the first threshold value; and in a third prediction process performed when the depth is greater than the second threshold value, using the intra prediction.