Octree Decoding Order Selection for Lower-Memory Point Cloud Processing
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Solution Overview
Problem
Decoding octree data in a breadth-first order can lead to increased memory requirements and suboptimal processing performance due to dependency relationships and the need to hold information about all nodes in previous layers, which may not be efficient depending on hardware performance.
Innovation Solution
An image processing apparatus and method that allows decoding of octree data in various processing orders by initializing the context for each layer of the octree and selecting between breadth-first and depth-first orders for decoding, enabling more flexible and efficient processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If decoding is performed in a breadth-first order, then the encoded data can be decoded following the encoding order, but the memory capacity required for storing data becomes larger
Solution Approach 1:
The patent makes the decoding order dynamic and selectable rather than fixed. The decoding unit can adaptively choose between breadth-first order and depth-first order based on memory capacity constraints and performance requirements, transforming a static decoding process into a flexible one that responds to different operational conditions
Solution Approach 2:
The patent changes the processing order parameter from a fixed breadth-first approach to a selectable parameter that can be set to either breadth-first or depth-first order. This parameter change allows the system to optimize between memory usage and decoding accuracy depending on the specific application requirements
2Reliability
If decoding is performed in a breadth-first order, then the encoding and decoding consistency is maintained, but the processing order may not be optimal depending on hardware performance
Solution Approach 1:
The patent introduces dynamic selectability in the decoding order, allowing the system to adapt to different hardware performance characteristics. By making the decoding order a configurable parameter rather than a fixed constraint, the system can optimize processing efficiency for specific hardware while maintaining compatibility through the option of breadth-first order
Solution Approach 2:
The patent makes the decoding unit universal by enabling it to perform both breadth-first decoding (maintaining encoding-decoding consistency) and depth-first decoding (optimizing for hardware performance). This multi-functionality allows a single decoding unit to serve diverse application scenarios with different performance requirements
3Adaptability or versatility
If the context is not initialized for each layer, then the processing is simpler, but the decoding cannot support various processing orders
Solution Approach 1:
The patent segments the context initialization process by layer, initializing the context for each layer of the octree separately. This segmentation enables the decoding unit to handle different layers independently, which is essential for supporting both breadth-first and depth-first decoding orders while managing complexity through structured organization
Data Source
AI summary
The present disclosure relates to an image processing apparatus and a method that enable decoding of encoded data of an octree in various processing orders. The octree corresponding to point cloud data is encoded after the context is initialized for each layer of the octree. Further, a breadth-first order or a depth-first order is selected as the decoding order for the encoded data of the octree corresponding to point cloud data, and the encoded data is decoded in the selected decoding order. The present disclosure can be applied to an image processing apparatus, an electronic apparatus, an image processing method, a program, or the like, for example.