Point Cloud Data Block Decoding with Adaptive Encoding Parameters
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Solution Overview
Problem
The decoding of bit streams from point cloud data is inefficient due to large data sizes, leading to prolonged processing times and low decoding efficiency.
Innovation Solution
Implementing non-equal length encoding for point cloud data blocks, where the encoding parameter is adaptively determined based on the signal features of the data block, reducing redundancy and optimizing the encoding data size for faster decoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If equal length encoding is used for point cloud data blocks, then the encoding process is simple and uniform, but the data size becomes large and decoding efficiency decreases
Solution Approach 1:
The patent applies local quality by using non-equal length encoding where different data blocks are encoded with different code lengths based on their signal features. Data blocks with similar characteristics are grouped together and assigned appropriate encoding parameters, allowing the encoding scheme to adapt locally to the specific properties of each data block rather than using a uniform approach throughout.
Solution Approach 2:
The patent implements parameter changes by dynamically adjusting encoding parameters based on signal features of data blocks. The system determines target encoding parameters according to the characteristics of the to-be-coded signal, such as signal variance or energy distribution, and uses these parameters to control the encoding process, thereby optimizing the balance between data size and decoding efficiency.
2Quantity of substance
If non-equal length encoding is used to reduce data size, then decoding efficiency improves, but the device complexity increases due to adaptive parameter determination
Solution Approach 1:
The patent applies preliminary action by pre-defining multiple sets of encoding parameters that can be selected based on signal features. Instead of performing complex real-time calculations to determine encoding parameters, the system prepares parameter sets in advance and selects the appropriate set based on the characteristics of the data block being encoded, thereby reducing the computational complexity during the actual encoding process.
Solution Approach 2:
The patent implements feedback by using the signal features of data blocks to dynamically adjust and select encoding parameters. The encoding process incorporates feedback from the analyzed signal characteristics, allowing the system to adaptively choose the most appropriate encoding parameters for each data block, thus optimizing the encoding efficiency while managing device complexity through intelligent parameter selection.
Data Source
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AI summary
Disclosed in the embodiments of the present application are a method and apparatus for decoding point cloud data, a method and apparatus for encoding point cloud data, and a storage medium and a device. The embodiments of the present application can be applied to scenarios such as cloud technology, intelligent traffic and aided driving. The decoding method comprises: acquiring encoded data of a data block to be processed in point cloud data; according to a target encoding parameter corresponding to said data block, determining a target decoding parameter of said data block; and decoding the encoded data according to the target decoding parameter, so as to obtain a decoded signal of said data block. By means of the present application, the decoding efficiency for a data block in point cloud data can be improved.