Spectral Coefficient Arithmetic Coding With Unified Context PDFs

Solution Overview

Problem

Arithmetic coding for multimedia data compression faces challenges with high encoding/decoding latency and memory capacity requirements due to the vast number of contexts and corresponding probability density functions needed for effective compression.

Innovation Solution

The method uses preceding spectral coefficients to determine context classes, which are then mapped to probability density functions for arithmetic encoding/decoding, employing non-uniform quantization to group similar contexts and reduce the number of functions needed, thereby decreasing latency and memory requirements.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of information

If a large number of contexts and corresponding probability density functions are used for arithmetic coding, then compression efficiency is improved, but encoding/decoding latency and memory capacity requirements increase

Engineering Contradiction:

Improvecompression efficiencyVSAvoidencoding/decoding latency

Core Design Contradiction:

Loss of informationVSLoss of time

Solution Approach 1:

Multiple probability density functions that correspond to different contexts are merged into a single unified probability density function. This unified PDF is constructed by combining the individual PDFs weighted by the probability of each context occurring, thereby reducing the number of PDFs that need to be stored and processed while maintaining compression efficiency.

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

A single unified probability density function is designed to serve multiple contexts that previously required separate PDFs. This universal PDF can adapt to different spectral coefficient patterns by incorporating context information from neighboring coefficients, eliminating the need for multiple specialized PDFs and reducing memory requirements.

Inventive Principle:

Principle #6Universality (Multi-functionality)

2Loss of information

If a large number of contexts and corresponding probability density functions are used for arithmetic coding, then compression efficiency is improved, but memory capacity requirements increase

Engineering Contradiction:

Improvecompression efficiencyVSAvoidmemory capacity requirements

Core Design Contradiction:

Loss of informationVSQuantity of substance

Solution Approach 1:

Multiple probability density functions that correspond to different contexts are merged into a single unified probability density function. This unified PDF is constructed by combining the individual PDFs weighted by the probability of each context occurring, thereby reducing the number of PDFs that need to be stored and processed while maintaining compression efficiency.

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

A single unified probability density function is designed to serve multiple contexts that previously required separate PDFs. This universal PDF can adapt to different spectral coefficient patterns by incorporating context information from neighboring coefficients, eliminating the need for multiple specialized PDFs and reducing memory requirements.

Inventive Principle:

Principle #6Universality (Multi-functionality)

3Loss of information

If a large number of contexts and corresponding probability density functions are used for arithmetic coding, then compression efficiency is improved, but device complexity increases

Engineering Contradiction:

Improvecompression efficiencyVSAvoidencoding/decoding complexity

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

Multiple probability density functions that correspond to different contexts are merged into a single unified probability density function. This unified PDF is constructed by combining the individual PDFs weighted by the probability of each context occurring, thereby reducing the number of PDFs that need to be stored and processed while maintaining compression efficiency.

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The approach changes from selecting among multiple discrete PDFs based on context to using a continuous unified PDF that adapts to different contexts through parameter adjustment. The unified PDF uses context information from neighboring spectral coefficients to dynamically adjust its parameters, simplifying the decision logic while maintaining adaptability.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS11381249B2Arithmetic encoding/decoding of spectral coefficients using preceding spectral coefficients

Publication Date: 2022.07.05 DOLBY LABORATORIES LICENSING CORP

AI summary

The invention proposes a method and a device for arithmetic encoding of a current spectral coefficient using preceding spectral coefficients. The preceding spectral coefficients are already encoded, and both the preceding and current spectral coefficients are comprised in one or more quantized spectra resulting from quantizing a time-frequency-transform of video, audio or speech signal sample values.