3D Point Attribute Coding Using Shared Values to Cut Bitstream Size
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Solution Overview
Problem
Existing three-dimensional data encoding and decoding methods lack efficient coding techniques, leading to high data volume and inefficient transmission and storage of three-dimensional data.
Innovation Solution
The proposed method involves encoding geometry information of three-dimensional points and generating bitstreams with first and second information items, where the first information indicates encoded attribute values and the second information indicates common attribute values among points, reducing redundant data transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all attribute values of three-dimensional points are encoded individually, then complete attribute information is preserved, but data volume increases and coding efficiency decreases
Solution Approach 1:
The patent merges identical attribute values by encoding them once with a common value identifier rather than encoding each occurrence separately. This combining approach preserves complete attribute information while significantly reducing the total data volume in the bitstream.
Solution Approach 2:
The patent changes the encoding parameter from individual attribute values to a combination of common value identifiers and occurrence counts. This parameter transformation allows the system to represent multiple identical attributes more compactly while maintaining information completeness.
2Measurement precision
If all attribute values of three-dimensional points are encoded individually, then accurate representation is achieved, but transmission and storage efficiency deteriorates
Solution Approach 1:
By merging identical attribute values into a single encoded entry with a common value identifier, the patent maintains accurate attribute representation while improving transmission efficiency through reduced data volume.
Solution Approach 2:
The patent uses reference copying where identical attribute values are stored once and then referenced multiple times through identifiers. This copying mechanism preserves representation accuracy while significantly reducing the amount of data that needs to be transmitted.
3Quantity of substance
If redundant attribute data is eliminated, then data compression is improved, but decoding complexity increases
Solution Approach 1:
The patent performs preliminary grouping and identification of common attribute values during the encoding phase. This preliminary action organizes the data in a structured manner that simplifies the decoding process, reducing the complexity burden despite the compression achieved.
Solution Approach 2:
The encoding process incorporates feedback mechanisms that identify and flag common attribute values, creating a structured representation that guides the decoding process. This feedback-based approach maintains manageable decoding complexity while achieving effective compression.
Data Source
AI summary
A three-dimensional data encoding method includes: encoding geometry information of three-dimensional points; generating a first bitstream including first information indicating encoded values when a value of an attribute of each of the three-dimensional points is encoded to generate the encoded values; and generating a second bitstream including second information indicating a common value of the attribute which is common between the three-dimensional points when the value of the attribute of each of the three-dimensional points is not encoded.