Adaptive Vector Quantization for Matrix Coefficients
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Solution Overview
Problem
Existing audio and video encoding technologies face inefficiencies in encoding large numbers of matrix coefficients, particularly in choosing suitable vector quantization schemes for diverse input signals, leading to limited encoding efficiency and increased complexity.
Innovation Solution
An encoder and decoder system that dynamically generates signal matrices, groups matrix coefficients into partition vectors, and selects optimal vector quantization schemes based on adaptive methods, including common-gain-split-shape, direct, gain-shape, and gain-shape-split schemes, to optimize encoding and decoding processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If scalar quantization or one-dimensional vector quantization is used to quantize a large number of matrix coefficients, then the encoding process is simple, but the encoding efficiency is limited and not impressive
Solution Approach 1:
The patent segments the large matrix coefficients into multiple sub-vectors or groups, and applies separate quantization to each group. This allows the system to achieve better encoding efficiency by treating different parts of the matrix differently, while maintaining manageable complexity through the segmented approach.
Solution Approach 2:
The patent transitions from scalar quantization (1D) and one-dimensional vector quantization to multi-dimensional vector quantization approaches. By quantizing groups of coefficients together in higher dimensions, the system achieves significantly improved encoding efficiency while managing complexity through structured grouping.
2Productivity
If several state-of-the-art vector quantization schemes are employed to encode a large number of matrix coefficients, then the encoding efficiency improves, but the difficulty in choosing one particular scheme suitable for a set of common input signals increases
Solution Approach 1:
The patent implements dynamic scheme selection that adapts to the characteristics of the input signal. Different vector quantization schemes are chosen based on the specific properties of the matrix coefficients being encoded, allowing the system to optimize for each input type rather than using a fixed scheme for all cases.
Solution Approach 2:
The patent changes quantization parameters such as the number of bits allocated to different coefficient groups, the grouping structure, and the specific quantization algorithm used, based on the statistical properties of the input signal. This allows optimal encoding efficiency for diverse input types without requiring manual scheme selection.
3Productivity
If pre-processing is performed on the matrix itself prior to applying a VQ scheme, then the encoding performance may be improved, but the device complexity and processing overhead increase
Solution Approach 1:
The patent performs preliminary actions such as sorting, grouping, or transforming the matrix coefficients before applying vector quantization. These pre-processing steps are designed to organize the data in a way that maximizes the effectiveness of the subsequent quantization, achieving better performance with relatively simple preprocessing operations.
Data Source
AI summary
A method for encoding an input signal comprising signal frames into quantized bits is disclosed, the method comprises generating, for each frame of the input signal, a signal matrix comprising matrix coefficients obtained from that frame, grouping the matrix coefficients of each signal matrix into a plurality of partition vectors, and for each partition vector, selecting one vector quantization scheme from among a plurality of vector quantization schemes and quantizing that partition vector according to the selected vector quantization scheme to obtain the quantized bits. In an adaptive mode, the method comprises grouping differently the matrix coefficients obtained from different frames, and/or selecting different vector quantization schemes for partition vectors obtained from different frames.