HOA Non-Differential Gain Coding for Random Access
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The existing compression methods for Higher Order Ambisonics (HOA) representations lack an efficient way to determine the minimum number of bits required for representing non-differential gain values, which is crucial for random access and decoding, due to the absence of constraints on the value ranges in the MPEG-H 3D audio document.
Innovation Solution
Establishing an inter-relation between the value range of the input HOA representation and the potential maximum gains of signals before gain control processing, allowing for efficient coding of exponents to base '2' for describing total absolute amplitude changes, and verifying if the HOA representation satisfies the required value range constraints for correct compression.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If gain control processing is applied to compress HOA representations, then the bit rate is reduced and compression efficiency is improved, but the determination of minimum bits for non-differential gain values becomes complex and inefficient due to lack of value range constraints
Solution Approach 1:
The patent establishes specific value range constraints for HOA coefficient sequences (e.g., maximum amplitude of 0.5 or 1.0) and derives corresponding maximum gain values from these constraints. By changing the parameter definition to include explicit value range limits, the system can determine the minimum number of bits for non-differential gain values using straightforward formulas based on the maximum gain, thereby reducing complexity while maintaining compression efficiency.
2Measurement precision
If the number of expansion coefficients O is increased to improve spatial resolution, then the HOA representation quality is improved, but the total bit rate increases quadratically making transmission impractical
Solution Approach 1:
The patent extracts and separates the gain control information (non-differential gain values) from the main HOA coefficient data. By taking out the amplitude information and encoding it separately with optimized bit allocation based on derived constraints, the system reduces the overall bit rate requirement while preserving the spatial resolution quality provided by the full set of expansion coefficients.
Solution Approach 2:
The patent changes the representation parameter by introducing constrained value ranges for HOA coefficients and deriving maximum gain values therefrom. This parameter change enables more efficient encoding of amplitude information, reducing the bit rate required to transmit high-order HOA representations with improved spatial resolution.
3Productivity
If differential gain values are used to describe amplitude changes between frames, then the coding efficiency is improved for sequential decoding, but random access becomes difficult without total absolute amplitude change information
Solution Approach 1:
The patent segments the gain information into two parts: differential gain values for sequential frames and non-differential gain values (total absolute amplitude changes) for random access. By dividing the gain information representation this way, the system maintains coding efficiency through differential encoding while enabling random access through the inclusion of cumulative gain values that allow independent frame decoding.
Solution Approach 2:
The non-differential gain values act as an intermediary element that bridges the gap between differential encoding efficiency and random access requirements. These total absolute amplitude change values serve as a mediator that allows the decoder to reconstruct proper amplitude levels when accessing frames out of sequence, without requiring decoding of all previous frames.
Data Source
Figure 1A~1B
Figure 2A~2B
Figure 3~4
AI summary
When compressing an HOA data frame representation, a gain control (15, 151) is applied for each channel signal before it is perceptually encoded (16). The gain values are transferred in a differential manner as side information. However, for starting decoding of such streamed compressed HOA data frame representation absolute gain values are required, which should be coded with a minimum number of bits. For determining such lowest integer number (βe) of bits the HOA data frame representation (C(k)) is rendered in spatial domain to virtual loudspeaker signals lying on a unit sphere, followed by normalisation of the HOA data frame representation (C(k)) . Then the lowest integer number of bits is set to βe=⌈log2⌈log2KMAX⋅O⌉+1⌉.