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 for 360-degree images in virtual and augmented reality, requiring improved performance in image encoding and decoding, particularly for 360-degree images.
Innovation Solution
A method for decoding 360-degree images involves generating a predicted image using syntax information, combining it with a residual image, and reconstructing the image in a projection format, utilizing projection formats like ERP, CMP, OHP, and ISP, and performing image expansion based on partitioning units to enhance compression performance.
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 for handling the massive data generated by multi-view images
Solution Approach 1:
The patent divides the 360-degree image into multiple projection formats (ERP, CMP, OHP, ISP) and processes each format with optimized encoding/decoding methods. The image is segmented into multiple view images captured by different cameras, allowing parallel processing and reducing the computational burden on a single processing unit.
Solution Approach 2:
The patent applies different encoding parameters and processing methods according to the specific projection format being used. By changing the processing parameters to match the characteristics of each projection format (e.g., equi-rectangular, cubic, octahedral, icosahedral), the system optimizes processing performance for each type of 360-degree image representation.
2Manufacturing precision
If high-resolution and high-quality images are processed for virtual reality and augmented reality, then the image quality improves, but the amount of data generated increases massively
Solution Approach 1:
The patent creates multiple view images from a single 360-degree scene by simulating different camera positions and angles. These virtual camera views are generated through image processing algorithms that replicate what multiple physical cameras would capture, reducing the need for actual multi-camera setups while maintaining high image quality.
Solution Approach 2:
The patent transforms the 360-degree spherical image into multiple 2D projection formats (equi-rectangular, cubic, octahedral, icosahedral). This dimensional transformation allows the three-dimensional spherical data to be represented in two-dimensional formats that are more efficient for display and processing, reducing data volume while preserving image quality.
3Reliability
If multiple cameras are used to capture multi-view images for 360-degree images, then the realism for virtual reality and augmented reality improves, but the amount of data generated increases massively
Solution Approach 1:
The patent develops a universal encoding and decoding framework that handles multiple projection formats (ERP, CMP, OHP, ISP) and multiple view configurations through a single integrated system. This multi-functional approach allows the same processing pipeline to handle different camera arrangements and projection types, improving realism across various VR/AR applications without requiring separate processing systems for each configuration.
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.