360-Degree Image Decoding With Projection Scaling Offsets
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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 in specific projection formats like ERP, CMP, and OHP, while utilizing motion vector candidates and reference pictures for enhanced compression.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multi-view images are captured with a plurality of cameras for 360-degree images, then the quality and realism of virtual reality and augmented reality services are improved, but the amount of data generated increases massively
Solution Approach 1:
The 360-degree image is divided into multiple projection faces (e.g., cube map projections with 6 faces). Each face is processed and encoded independently, allowing for more efficient compression and management of the large data volume while maintaining overall image quality
Solution Approach 2:
The patent transforms the 360-degree spherical image into multiple 2D projection planes (ERP, CMP, OHP formats). This dimensional transformation enables standard 2D compression techniques to be applied effectively, reducing the data volume while preserving the immersive 360-degree viewing experience
2Reliability
If high-resolution images are processed for virtual reality and augmented reality, then the realism and quality of the service are improved, but the performance of the image processing system becomes insufficient
Solution Approach 1:
The image processing is segmented into multiple independent projection face processing units. Each face can be processed in parallel, significantly improving processing throughput and system performance while maintaining high resolution and quality
Solution Approach 2:
The patent applies selective processing to different regions of the 360-degree image based on importance. High-resolution processing is applied to critical regions (e.g., front-facing views), while less critical regions use reduced resolution, improving overall system performance while maintaining acceptable quality
3Ease of manufacture
If conventional image encoding methods are used for 360-degree images, then the processing is simple, but the compression performance is insufficient for large data volumes
Solution Approach 1:
The patent performs preliminary projection and reformatting of the 360-degree image into standard projection formats (ERP, CMP, OHP) before encoding. This preliminary transformation enables the use of efficient, standardized compression algorithms that achieve superior compression ratios while keeping the actual encoding process relatively simple
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.