Temporal Quantisation Control for Scalable Signal Encoding

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Solution Overview

Problem

Existing signal processing systems face inefficiencies in bitrate allocation and quality enhancement for compressed signals, particularly in scalable encoding techniques, where large amounts of data are stored and transmitted, especially with the increasing demand for higher quality video content.

Innovation Solution

The system derives quantisation parameters based on the similarity between data elements from different time samples of a signal, allowing for dynamic bitrate allocation and efficient quantisation, thereby improving visual quality and reducing data transmission requirements.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If scalable encoding techniques are used to maintain multiple quality levels, then signal quality and adaptability are improved, but data quantity and transmission bandwidth requirements increase

Engineering Contradiction:

Improvesignal quality adaptabilityVSAvoiddata quantity

Core Design Contradiction:

Adaptability or versatilityVSQuantity of substance

Solution Approach 1:

The patent dynamically changes quantisation parameters based on temporal similarity measures between consecutive time samples. By adjusting the quantisation step size according to how much the signal changes over time, the system adapts the data representation to the actual signal characteristics, reducing redundant information while maintaining quality where needed

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The system employs dynamic bitrate allocation where quantisation parameters are not fixed but adapt in real-time based on the derived temporal similarity measures. This allows the encoding strategy to flexibly respond to varying signal complexity across different time samples, optimizing the balance between quality and data quantity

Inventive Principle:

Principle #15Dynamics

2Manufacturing precision

If higher quality video content is transmitted, then visual quality is improved, but transmission bandwidth and data requirements increase

Engineering Contradiction:

Improvevisual qualityVSAvoidtransmission data

Core Design Contradiction:

Manufacturing precisionVSQuantity of substance

Solution Approach 1:

The patent dynamically adjusts quantisation parameters based on temporal similarity measures between consecutive time samples. By adjusting the quantisation step size according to how much the signal changes over time, the system adapts the data representation to the actual signal characteristics, reducing redundant information while maintaining quality where needed

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

Different quantisation parameters are applied to different time samples based on their individual temporal similarity characteristics. Time samples with low change (high similarity) receive coarser quantisation, while those with high change (low similarity) receive finer quantisation, optimizing quality distribution across the entire signal

Inventive Principle:

Principle #3Local quality

3Ease of manufacture

If uniform quantisation is applied to all time samples, then processing simplicity is maintained, but bitrate allocation efficiency decreases

Engineering Contradiction:

Improveprocessing simplicityVSAvoidbitrate allocation efficiency

Core Design Contradiction:

Ease of manufactureVSProductivity

Solution Approach 1:

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The patent calculates temporal similarity measures between consecutive time samples before performing quantisation. This preliminary analysis of signal characteristics allows the system to pre-determine appropriate quantisation parameters for each time sample, ensuring optimal bitrate allocation before the actual compression process

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS10735024B2Data processing apparatuses, methods, computer programs and computer-readable media

Publication Date: 2020.08.04 V NOVA INT LTD

AI summary

A first value of a first data element in a first set of data elements is obtained, the first set of data elements being based on a first time sample of a signal. A second value of a second data element in a second set of data elements is obtained, the second set of data elements being based on a second, later time sample of the signal. A measure of similarity is derived between the first value and the second value. Based on the derived measure, a quantisation parameter useable in performing quantisation on data based on the first time sample of the signal is determined. Output data is generated using the quantisation parameter.