Output Layer Signaling for Adaptive-Resolution Video Coding
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Solution Overview
Problem
Existing video coding technologies struggle to efficiently handle semantically independent picture parts with different adaptive resolution settings, particularly in applications like 360 coding and surveillance, requiring improved reference picture resampling and adaptive resolution coding signaling.
Innovation Solution
A method and system for encoding video streams that partition data into layers, using syntax elements to determine whether a picture is to be output based on output layer set signaling, allowing for adaptive resolution changes and efficient resampling of reference pictures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If video streams are encoded with multiple layers and adaptive resolution changes, then video quality is maintained while reducing bandwidth and storage requirements, but device complexity increases due to layer partitioning and output layer set signaling
Solution Approach 1:
The video stream is partitioned into multiple layers with different resolution settings, allowing selective encoding and decoding of picture parts. The picture is divided into regions that can be independently coded at different resolutions, enabling efficient bandwidth utilization while maintaining quality where needed.
Solution Approach 2:
The output layer set is dynamically determined based on syntax elements in the bitstream. The decoder adapts which layers to output by parsing output layer set signaling, allowing flexible resolution adaptation without fixed predetermined layer configurations.
2Adaptability or versatility
If reference pictures are resampled for different resolutions within a CVS, then adaptive resolution changes are enabled, but manufacturing precision deteriorates due to potential distortion in resampled reference pictures
Solution Approach 1:
Different regions of the picture are assigned different resolution settings and layer configurations. Semantically important regions can be maintained at higher resolutions while less important regions use lower resolutions, optimizing overall quality while enabling adaptive resolution changes.
Solution Approach 2:
Reference pictures are resampled and copied at different resolutions for use in prediction. Multiple versions of reference pictures at different resolutions are maintained and selected based on the current picture's resolution requirements, preserving accuracy where needed.
3Loss of energy
If lossy compression is applied to reduce bandwidth requirements, then compression ratio increases, but loss of information increases due to distortion between original and reconstructed signals
Solution Approach 1:
Different quantization parameters and compression settings are applied to different layers and picture regions. Important regions use higher quality settings with less compression, while less important regions use higher compression ratios, optimizing the balance between bandwidth efficiency and information preservation.
Data Source
AI summary
Systems and methods for coding and decoding are provided. A method includes encoding a video stream including video data partitioned into a plurality of layers, wherein the encoding includes determining whether a first picture of the video stream is to be output based on a syntax element that indicates a mode of output layer set signaling.


