3D LUT Residue Encoding for Lower Video Transmission Load
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Solution Overview
Problem
Existing methods for encoding and decoding 3D Look-Up Tables (LUTs) for color transforms in scalable video decoding are inefficient due to the large data set required, which is not effectively managed, leading to high transmission costs and inefficiencies.
Innovation Solution
A method for encoding and decoding 3D LUTs using a lattice structure, such as an octree, where residues are calculated and entropy encoded, reducing data transmission by predicting color values from neighboring vertices and only encoding significant residues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a 3D LUT is used to describe the Color Mapping Function for precise color transformation, then the accuracy of color transformation is improved, but the data size increases significantly requiring efficient encoding
Solution Approach 1:
The 3D LUT is divided into multiple octants (8 sub-regions), and each octant is further subdivided into smaller sub-octants. This hierarchical segmentation allows the large 3D LUT to be processed and transmitted in smaller, more manageable units, reducing the immediate data transmission burden while maintaining the ability to represent precise color transformations.
Solution Approach 2:
The patent introduces a hierarchical dimension to the traditional 3D LUT structure by creating multiple levels of octant decomposition. This transforms the flat 3D space into a multi-level tree structure, where each level provides coarser or finer granularity, enabling progressive transmission and decoding of color transformation data.
2Reliability
If all vertex values of the 3D LUT are encoded, then the complete color transformation information is preserved, but the transmission efficiency decreases due to the huge amount of data
Solution Approach 1:
The patent extracts only the essential color transformation information from each octant by identifying and encoding representative vertices and their associated color mapping parameters. Instead of transmitting all vertex data, only the critical parameters needed to reconstruct the color transformation are extracted and transmitted, significantly reducing data volume while preserving transformation accuracy.
Solution Approach 2:
The patent transforms the complete vertex data representation into a parameter-based representation. Each octant is described by a set of parameters (such as vertex coordinates, color values, and transformation coefficients) rather than transmitting all individual vertex values. This parameterization reduces the data required to describe the same color transformation information.
3Quantity of substance
If a linear transform model (Gain-Offset) is used for the Color Mapping Function, then the data required is reduced to 12 parameters, but the precision of color transformation is compromised
Solution Approach 1:
The patent implements a dynamic adaptation mechanism where the complexity of the color transformation model is adjusted based on the specific requirements of each octant. For regions where linear transformation is sufficient, simpler models are used, while for regions requiring higher precision, more complex non-linear transformations are applied. This dynamic approach optimizes the balance between data size and transformation accuracy.
Solution Approach 2:
Different octants can use different transformation models and parameter sets based on their local characteristics. Each octant is independently processed, allowing the system to apply the appropriate level of complexity locally rather than using a uniform approach for the entire 3D LUT. This local optimization ensures high accuracy where needed while minimizing data transmission in regions where simpler models suffice.
Data Source
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AI summary
A method for encoding a LUT defined as a lattice of vertices is disclosed. At least one value is associated with each vertex of the lattice. The method comprises for a current vertex: - predicting the at least one value associated with said current vertex from another value which is for example obtained from reconstructed values associated with neighboring vertices; and - encoding in a bitstream at least one residue computed between the at least one value of the current vertex and its prediction in a bitstream.