Projection-Format Image Decoding for 360-Degree Compression
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Solution Overview
Problem
Existing image processing systems struggle with the massive data generated from processing multi-view images for 360-degree images in 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 ERP, CMP, and ISP, while utilizing motion vector candidates and reference pictures for enhanced compression.
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 when handling massive data from multi-view images
Solution Approach 1:
The 360-degree image is divided into multiple projection formats (ERP, CMP, OHP, ISP) and processed separately. The decoding method segments the bitstream into different projection format components, allowing parallel processing of multiple view angles and reducing the computational burden on single-threaded systems.
Solution Approach 2:
The patent transforms the processing approach by introducing projection format dimensions. Instead of processing the massive 360-degree image data as a single entity, the system converts it into multiple 2D projection planes (cube faces, octahedron faces, icosahedron faces), enabling standard image processing algorithms to work efficiently on each dimension independently.
2Measurement precision
If high-resolution 360-degree images are processed, then the image quality is improved, but the data amount increases massively
Solution Approach 1:
The patent combines multiple low-resolution projection formats into a single high-resolution 360-degree image. By merging the decoded ERP, CMP, OHP, and ISP projection data with appropriate weighting and blending algorithms, the system achieves high-resolution output without requiring all input data to be at full resolution simultaneously.
Solution Approach 2:
The system dynamically changes resolution parameters across different projection formats. Not all projection formats are decoded at the same resolution level; instead, the method adjusts the resolution parameter for each projection type based on its importance and the viewer's likely focus area, reducing total data volume while maintaining perceived image quality.
3Adaptability or versatility
If multiple projection formats are supported for 360-degree images, then the versatility is improved, but the device complexity increases
Solution Approach 1:
The decoding apparatus is designed with universal functionality to handle multiple projection formats (ERP, CMP, OHP, ISP) through a single integrated architecture. The system uses a unified decoding framework that can adaptively process different projection types without requiring separate dedicated hardware for each format, reducing overall device complexity.
Solution Approach 2:
The patent introduces an intermediary conversion layer that transforms different projection formats into a common intermediate representation before final rendering. This mediator approach allows the system to support multiple input formats while maintaining a simplified output pipeline, reducing the complexity burden on the final display system.
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.