Longitude-Latitude Map Division for 360 Video Encoding
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Solution Overview
Problem
Existing image processing methods for 360-degree panorama videos using longitude-latitude maps result in low encoding efficiency and bandwidth waste due to uniform division intervals, which do not account for varying pixel redundancy at different latitudes, leading to inefficient encoding and transmission.
Innovation Solution
The method involves performing horizontal and vertical divisions on the longitude-latitude map with varying division intervals based on latitude, allowing for different sub-area sizes and sampling rates, reducing pixel redundancy and bandwidth usage by downsampling high-latitude areas, and encoding these sub-areas independently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If uniform division intervals are used for encoding longitude-latitude map images, then encoding simplicity is maintained, but encoding efficiency deteriorates and bandwidth is wasted due to not accounting for varying pixel redundancy at different latitudes
Solution Approach 1:
The image is divided into multiple sub-areas based on latitude zones, with each zone having its own division interval. This segmentation allows different encoding strategies to be applied to different regions, improving overall encoding efficiency while maintaining manageable complexity through systematic organization.
Solution Approach 2:
Different division intervals are applied to different latitude regions: larger intervals for high-latitude areas with high redundancy, and smaller intervals for low-latitude areas with low redundancy. This local adaptation of encoding parameters optimizes the balance between image quality and bandwidth usage for each specific region.
2Device complexity
If uniform division intervals are used for encoding longitude-latitude map images, then encoding process complexity is reduced, but bandwidth usage increases due to transmitting redundant data from high-latitude areas
Solution Approach 1:
The division interval parameter is changed based on latitude: larger intervals are used for high-latitude regions where pixel redundancy is high, and smaller intervals are used for low-latitude regions where pixel redundancy is low. This parameter adaptation reduces the total amount of data to be transmitted while maintaining image quality where it matters most.
3Loss of energy
If larger division intervals are used for high-latitude areas, then bandwidth usage is reduced by downsampling redundant regions, but image detail quality may deteriorate in those areas
Solution Approach 1:
Different quality levels are applied to different latitude regions based on their visual importance and redundancy characteristics. High-latitude areas with large division intervals accept lower detail quality since they contain redundant information, while low-latitude areas with small division intervals maintain high detail quality where visual information is most critical.
Data Source
AI summary
An image processing method includes performing horizontal division and vertical division on a longitude-latitude map or a sphere map of a to-be-processed image to obtain sub-areas of the longitude-latitude map or the sphere map, where a division location of the horizontal division is a preset latitude, a division location of the vertical division is determined by a latitude, there are at least two types of vertical division intervals in an area formed by adjacent division locations of the horizontal division, and a vertical division interval is a distance between adjacent division locations of the vertical division, and encoding images of the sub-areas.