360-Degree Image Coding With Projection-Specific Inter Prediction
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Solution Overview
Problem
Existing image processing systems struggle with the massive data generated for 360-degree images in virtual and augmented reality, requiring improved performance in encoding and decoding methods.
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 in specific projection formats, utilizing motion vector candidates and image expansion based on partitioning units.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional image encoding/decoding methods are used for 360-degree images, then the processing can be performed with standard algorithms, but the performance is insufficient due to the massive amount of data generated
Solution Approach 1:
The 360-degree image is divided into multiple projection formats (ERP, CMP, OHP, ISP) and processed separately. The encoding apparatus performs image expansion and setting processes specific to each projection format, allowing the massive data to be handled in manageable segments rather than as a single large dataset.
Solution Approach 2:
The patent performs image expansion and projection format setting processes before the main encoding operation. By pre-processing the 360-degree image into various projection formats and performing necessary expansions, the system prepares the data in advance, reducing the computational burden during actual encoding and improving overall processing performance.
2Adaptability or versatility
If multiple projection formats are supported for 360-degree images, then the versatility of the system is improved, but the device complexity increases
Solution Approach 1:
The encoding apparatus is designed with multi-functional capabilities to handle multiple projection formats (ERP, CMP, OHP, ISP) within a single system. The image expansion unit and projection format setting unit can adaptively process different formats, allowing one device to serve multiple functions rather than requiring separate systems for each format.
Solution Approach 2:
The system dynamically adjusts its processing based on the input projection format. The image expansion and setting processes are configured to adapt to the specific characteristics of each projection format, allowing the device to optimize its operation for the current format being processed rather than being fixed to a single configuration.
3Measurement precision
If image expansion is performed on partitioning units for motion prediction, then the prediction accuracy is improved, but the processing time increases
Solution Approach 1:
The image expansion process is performed on partitioning units (tiles or slices) rather than on the entire image at once. This segmentation allows motion prediction to be conducted on smaller, manageable portions of the image, improving prediction accuracy through localized processing while reducing the time penalty compared to processing the whole image simultaneously.
Data Source
AI summary
A method of decoding an image, includes obtaining at least one offset for a picture, deriving a variable for scaling for the picture based on the at least one offset, and performing inter prediction based on the variable for scaling for the picture. The at least one offset is defined with a direction of scaling.