Inter-component Residual Prediction for Point Cloud Color Compression
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Solution Overview
Problem
Existing point cloud compression techniques are inefficient in encoding and decoding color values, leading to higher bit usage due to signaling full residual values, which can be reduced by predicting and scaling residual values.
Innovation Solution
Implementing a technique where G-PCC encoders and decoders use scaling factors to predict and encode residual values for color components, allowing for more accurate prediction and reduced bit usage by signaling the difference between actual and predicted values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If full residual values are signaled for each color component, then color accuracy is maintained, but bit usage increases
Solution Approach 1:
The patent applies preliminary action by predicting residual values for color components before encoding them. The encoder predicts the residual value of a second color component (e.g., B or R) based on the residual value of a first color component (e.g., G) that has already been encoded. This prediction allows the system to encode only the difference between the actual and predicted residual values, significantly reducing the number of bits needed while maintaining color accuracy.
Solution Approach 2:
The patent uses an intermediary approach by introducing a prediction mechanism that acts as a mediator between the actual residual values and the encoded values. The predicted residual value serves as an intermediate representation that captures the correlation between color components, allowing the system to encode only the residual difference rather than the full residual value, thus reducing bit usage while preserving color fidelity.
2Quantity of substance
If residual prediction between color components is implemented, then bit usage is reduced, but coding complexity increases
Solution Approach 1:
The patent applies parameter changes by modifying the residual values through scaling factors before encoding. The encoder scales the predicted residual value of the first color component to better match the statistical characteristics of the second color component's residual values. This parameter adjustment improves prediction accuracy and reduces the magnitude of residual differences that need to be encoded, thereby reducing bit usage while the complexity remains manageable through efficient mathematical operations.
3Measurement precision
If scaling factors are applied to residual values, then prediction accuracy improves, but computational complexity increases
Solution Approach 1:
The patent uses parameter changes by applying scaling factors to the predicted residual values to improve prediction accuracy. The scaling factors are derived from the statistical properties of the color components and are used to adjust the magnitude of the predicted residuals before computing the final encoded values. This approach improves prediction accuracy by accounting for the different variances in color component residuals, while the computational complexity is kept manageable through efficient scaling operations.
Data Source
AI summary
A device for decoding encoded point cloud data can be configured to, for a point of a point cloud, determine a first color value for a first color component based on a first predicted value and a first residual value; apply a scaling factor to the first residual value to determine a predicted second residual value, wherein the scaling factor has one or both of a non-integer value or an absolute value greater than one; for the point of the point cloud, receive a second residual value in the encoded point cloud data; determine a final second residual value based on the predicted second residual value and the received second residual value; and for the point of the point cloud, determine a second color value for a second color component based on a second predicted value and the final second residual value.