Non-Differential HOA Gain Coding for Random-Access Compression
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing HOA compression methods lack an efficient method to determine the lowest integer number of bits required for representing non-differential gain values, which is crucial for effective compression and random access in HOA data frame representations.
Innovation Solution
Establish an inter-relation between the value range of the input HOA representation and the potential maximum gains of the signals before gain control, determining the required bits for coding exponents to base '2' using a specific method involving mode matrices and normalizing the HOA data frames to ensure 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, but the determination of the lowest integer number of bits for representing non-differential gain values becomes complex and computationally intensive
Solution Approach 1:
The patent applies preliminary action by pre-determining the lowest integer number of bits (βe) required for representing non-differential gain values before the actual compression process. This is achieved through advance calculations involving mode matrices and signal amplitude analysis, allowing the system to prepare the optimal bit allocation in advance rather than computing it during real-time compression, thus reducing computational complexity while maintaining compression efficiency
Solution Approach 2:
The patent utilizes parameter changes by dynamically adjusting the number of bits allocated for gain value representation based on the specific characteristics of the HOA signal being compressed. By calculating the actual signal amplitude range and determining the minimum required bits accordingly, the system optimizes the balance between compression efficiency and reconstruction accuracy, rather than using a fixed bit allocation scheme
2Measurement precision
If the number of expansion coefficients O is increased to improve spatial resolution, then the quality of HOA representation improves, but the bit rate increases quadratically
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the bit allocation for different expansion coefficients based on their actual contribution to the signal. Instead of uniformly allocating bits to all O coefficients, the system analyzes the signal characteristics and allocates bits selectively, reducing the total bit rate while maintaining the spatial resolution provided by the higher order coefficients
Solution Approach 2:
The patent implements local quality by applying different bit allocation strategies to different groups of expansion coefficients based on their importance and characteristics. Critical coefficients that contribute most to spatial resolution receive adequate bit allocation, while less significant coefficients use fewer bits, thereby optimizing the overall bit rate for the given spatial resolution requirement
3Ease of operation
If random access is enabled in HOA data frames, then the usability of compressed HOA data improves, but additional side information must be transmitted increasing the bit rate
Solution Approach 1:
The patent applies preliminary action by pre-calculating and embedding the minimum required bit allocation for gain values as side information during the compression phase. This advance preparation ensures that random access points can be efficiently located and decoded without requiring excessive additional data, as the essential gain value representations are already optimally allocated in the compressed stream
Solution Approach 2:
The patent implements partial action by transmitting only the essential minimum side information required for random access functionality. Rather than including complete gain value data at all access points, the system transmits the minimal necessary information (exponents to base 2) that enables reconstruction at random access points, thereby reducing the overhead bit rate while maintaining random access capability
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⌉.