360-Degree Video Coding Using Adaptive Weighted Parameters
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for processing 360-degree video face inefficiencies due to non-uniform distortion when projecting three-dimensional video data to a two-dimensional format, leading to uneven quality across different regions, particularly in pole areas compared to equatorial areas.
Innovation Solution
Determining and applying adaptive parameters, such as weighted distortion, quantization parameters, and lambda values, based on the position and resolution of samples within the 360-degree video frames to optimize coding modes and improve compression efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If uniform quantization parameters are applied across all regions of 360-degree video, then encoding simplicity is maintained, but quality uniformity deteriorates due to non-uniform distortion in pole areas versus equatorial areas
Solution Approach 1:
The patent applies different quantization parameters to different regions of the 360-degree video frame based on their distortion characteristics. Pole areas with high distortion receive higher QP values (coarser quantization), while equatorial areas with low distortion receive lower QP values (finer quantization). This regional differentiation resolves the contradiction by sacrificing encoding simplicity to achieve quality uniformity across regions with different distortion properties.
2Manufacturing precision
If more bits are allocated to pole areas to compensate for distortion, then quality in pole areas improves, but compression efficiency deteriorates due to uneven bit distribution
Solution Approach 1:
The patent dynamically adjusts quantization parameters based on the spatial position and distortion characteristics of different regions. By changing the QP parameter according to location (higher QP for pole areas, lower QP for equatorial areas), the system achieves quality uniformity without requiring uniform bit allocation. This resolves the contradiction by optimizing the quality-bitrate tradeoff through parameter adaptation rather than uniform bit distribution.
3Manufacturing precision
If adaptive parameters are applied to different regions, then quality uniformity improves, but device complexity increases due to additional processing requirements
Solution Approach 1:
The patent divides the 360-degree video frame into different regions (pole areas and equatorial areas) and applies different processing parameters to each segment. This segmentation approach enables quality uniformity by treating high-distortion and low-distortion regions differently. The complexity is managed by using straightforward geometric region classification rather than complex adaptive algorithms, resolving the contradiction between quality uniformity and processing complexity.
Data Source
AI summary
Techniques and systems are provided for processing 360-degree video data. For example, a picture of the 360-degree video data can be obtained. The picture can include samples projected from a three-dimensional format to a two-dimensional format. A weight value can be determined for at least one sample of the picture. The weight value can be determined based at least on a position of the at least one sample in the picture. At least one adaptive parameter can be determined for the at least one sample using the determined weight value. The at least one adaptive parameter can include one or more of an adaptive weighted distortion, an adaptive weighted quantization parameter value, or an adaptive weighted lambda value. A cost associated with coding the at least one sample using one or more coding modes can be determined using the at least one adaptive parameter of the at least one sample.