360-Degree Image Decoding with Projection-Specific Motion Prediction
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Solution Overview
Problem
Existing image processing systems struggle with the massive data requirements of 360-degree images for virtual and augmented reality, necessitating improved performance in image encoding and decoding, particularly for high-resolution and ultra-high-definition 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 Equi-Rectangular, CubeMap, OctaHedron, and IcoSahedral, with image expansion and motion vector prediction 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 high-resolution and ultra-high-definition images
Solution Approach 1:
The 360-degree image is divided into multiple projection formats (ERP, CMP, OHP, ISP) and processed separately. Each projection format has its own encoding parameters and methods, allowing optimized compression for each segment while maintaining overall image quality
Solution Approach 2:
The patent performs image expansion and motion vector prediction before the main encoding process. By preparing predicted images and motion information in advance, the actual encoding requires fewer computations, improving compression performance without proportionally increasing complexity
2Measurement precision
If high-resolution and ultra-high-definition 360-degree images are processed, then image quality is improved, but the data volume increases massively
Solution Approach 1:
The patent changes the projection format parameters to suit different application requirements. By selecting appropriate projection formats (ERP for equirectangular, CMP for cube maps, etc.) and adjusting encoding parameters for each format, the system achieves efficient compression of high-resolution images while maintaining quality
Solution Approach 2:
The patent transforms the 360-degree spherical image into multiple 2D projection formats. This dimensional transformation allows standard 2D image compression techniques to be applied effectively, reducing the data volume of high-resolution 360-degree images while preserving visual quality
3Loss of energy
If image expansion is performed for motion prediction, then compression performance is improved, but processing time increases
Solution Approach 1:
The patent performs image expansion only for the regions and blocks that require motion prediction, rather than expanding the entire image. This partial action approach maintains compression efficiency while significantly reducing the total processing time required
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.