Network Abstraction Layer Subset Sizing for Lower-Latency Video Decoding
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Solution Overview
Problem
Existing video coding standards face challenges in reducing latency during the decoding process, particularly in handling complex video block structures and prediction techniques, leading to inefficiencies in video data processing.
Innovation Solution
Implementing techniques that signal a size constraint for subsets of network abstraction units, including slices of video data, to optimize decoding processes by constraining the size of video blocks and enhancing prediction accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If complex video block structures and prediction techniques are used, then video compression efficiency is improved, but decoding latency increases
Solution Approach 1:
The patent divides the video data into network abstraction unit subsets with constrained sizes, processing smaller segments independently to reduce decoding latency while maintaining compression efficiency through structured segmentation of video blocks
2Device complexity
If larger video blocks are processed, then fewer blocks need to be decoded, but decoding complexity and latency increase
Solution Approach 1:
The patent introduces size constraint parameters for network abstraction unit subsets, dynamically adjusting block processing parameters to optimize the balance between decoding complexity and latency by constraining subset sizes within defined limits
Data Source
AI summary
A method of signaling parameters for video data is disclosed. The method comprising: signaling a syntax element indicating a size constraint for subsets of a network abstraction layer unit including a slice of video data.