360-Degree Image Partitioning for High-Resolution Decoding
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Solution Overview
Problem
Existing image processing systems struggle with the massive data generated from processing multi-view 360-degree images for virtual and augmented reality, leading to insufficient performance in encoding and decoding high-resolution images.
Innovation Solution
A method for encoding and decoding 360-degree images that includes generating a predicted image using syntax information, combining it with a residual image, and reconstructing the image based on projection formats like Equi-Rectangular, CubeMap, OctaHedron, and IcoSahedral Projection, with image expansion performed on partitioning units using adjacent pixel information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If multi-view images are processed for 360-degree images, then the amount of data increases massively, but the performance of image processing system becomes insufficient
Solution Approach 1:
The patent divides the 360-degree image into multiple view images captured by different cameras, allowing independent processing and encoding of each view. This segmentation reduces the complexity of handling the complete 360-degree image as a single large data structure, enabling more efficient processing while maintaining the full 360-degree content.
Solution Approach 2:
The patent transforms 360-degree images into various projection formats (e.g., equirectangular projection, cube map projection, octahedron projection, icosahedral projection) that convert three-dimensional spherical data into two-dimensional representations. This dimensional transformation enables standard image processing techniques to be applied more effectively to 360-degree content.
2Measurement precision
If high-resolution images are processed, then image quality improves, but data volume increases and processing performance becomes insufficient
Solution Approach 1:
The patent applies different encoding parameters and processing techniques to different regions or views of the 360-degree image based on their specific characteristics and requirements. This allows optimization of image quality in critical areas while using more efficient processing for less critical areas, balancing overall quality and performance.
Solution Approach 2:
The patent employs various projection formats and encoding parameters that can be adjusted according to the specific requirements of the application. By changing parameters such as projection type, resolution levels, and encoding settings, the system can optimize between image quality and processing performance for different use cases.
Data Source
AI summary
A method for decoding an image includes receiving information on image partitioning for the image included in a bitstream; obtaining a plurality of image partitions included in the image based on the information on image partitioning; and decoding the plurality of image partitions. Each image partition comprises a plurality of default encoding parts, each default encoding part is selected from a plurality of candidate default encoding parts, each candidate default encoding part is composed of one or more encoding sub-units. The bitstream includes information on rotation of the image.