360-Degree Image Decoding Using Directional Scaling Offsets
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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, necessitating improved performance in image encoding and decoding, particularly for 360-degree 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 in a specific projection format, utilizing image expansion based on partitioning units and motion vector candidates to enhance compression performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If conventional image encoding methods are used for 360-degree images, then the encoding process is simple, but the compression performance is insufficient for large data volumes
Solution Approach 1:
The 360-degree image is divided into multiple projection formats (e.g., equirectangular, cube map, octahedron, icosahedron). The encoder selects the most appropriate projection format for different regions or entire images based on content characteristics, enabling optimized compression for each format's specific data patterns and reducing overall compression loss.
Solution Approach 2:
The patent dynamically adjusts encoding parameters including projection format selection, block size, and transformation types based on the characteristics of the 360-degree image content. This adaptive parameter adjustment allows the system to achieve better compression performance by matching encoding strategies to specific image features rather than using fixed conventional parameters.
2Reliability
If image processing is performed on full-resolution 360-degree images, then image quality is maintained, but processing time and computational resources increase significantly
Solution Approach 1:
The decoding process is segmented into parallel operations: multiple predicted images are generated simultaneously from different projection formats, then combined through weighted summation. This parallel processing approach maintains full-resolution image quality while reducing total processing time compared to sequential methods.
Solution Approach 2:
The encoder performs preliminary processing by converting the 360-degree image into multiple projection formats in advance and selecting the optimal format for different regions. This pre-processing reduces the computational burden during real-time decoding while maintaining image quality, as the most suitable data representation is already prepared beforehand.
3Loss of energy
If multiple projection formats are used for 360-degree images, then compression performance improves, but system complexity increases
Solution Approach 1:
The system dynamically selects and switches between different projection formats (equirectangular, cube map, octahedron, icosahedron) based on image content characteristics and encoding conditions. This parameter-based format selection allows the system to achieve improved compression efficiency for different types of 360-degree content while managing system complexity through adaptive rather than exhaustive processing of all formats simultaneously.
Solution Approach 2:
Different projection formats are applied to different regions or portions of the 360-degree image based on local content characteristics. For example, regions with specific geometric features may use cube map projection while other regions use equirectangular projection. This localized approach improves overall compression efficiency by matching format to content while reducing system complexity compared to processing entire images in all formats.
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.