360-Degree Image Encoding With Projection Format Segmentation
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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 image encoding and decoding.
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 various projection formats, with image expansion based on partitioning units and motion vector candidates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If 360-degree images are processed using conventional image processing systems, then the images can be encoded and decoded, but the processing performance is insufficient due to the massive amount of data generated
Solution Approach 1:
The 360-degree image is divided into multiple projection format images (e.g., ERP, CMP, OHP, ISP formats). Each projection format image is processed independently through encoding and decoding, which reduces the processing burden on the system and improves overall processing performance while handling the massive data量
Solution Approach 2:
The patent transforms the processing approach by introducing projection format conversion as an additional dimension. Instead of processing the entire 360-degree image directly, the system converts between different projection formats (ERP to CMP, OHP, ISP, etc.), enabling more efficient processing and storage of the massive data through dimensional transformation
2Adaptability or versatility
If multiple projection formats are supported for 360-degree images, then the adaptability and versatility are improved, but the device complexity increases
Solution Approach 1:
The image processing system is designed with multi-functionality to handle multiple projection formats (ERP, CMP, OHP, ISP). The same encoding and decoding apparatus can process images in different projection formats by selecting appropriate conversion methods, eliminating the need for separate processing systems for each format and thereby reducing overall device complexity while maintaining high adaptability
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.