Projection-Based 360-Degree Image Decoding for Compression Bottlenecks
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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 involves generating a predicted image using syntax information, combining it with a residual image, and reconstructing the image in specific projection formats like ERP, CMP, OHP, or ISP, with image expansion based on partitioning units and motion vector prediction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multi-view images are captured with multiple cameras for 360-degree images, then the realism and quality of virtual reality and augmented reality improve, 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 faces), and each face is processed independently through encoding and decoding operations. This segmentation allows the large data volume to be managed in smaller, more efficient units while maintaining overall image quality
Solution Approach 2:
The patent uses reference pictures and motion compensation to generate predicted images that are combined with residual images. This copying approach allows efficient representation of redundant information across different views and time points, reducing the actual data that needs to be transmitted and stored
2Area of stationary object
If the amount of data for 360-degree images increases massively, then the coverage and resolution improve, but the performance of image processing systems becomes insufficient
Solution Approach 1:
The patent performs motion estimation and generates predicted images before the actual decoding process. By preparing reference pictures and motion vectors in advance, the system reduces the computational burden during real-time decoding, improving processing performance while maintaining high-resolution output
Solution Approach 2:
The encoding and decoding process adapts dynamically by using motion-compensated prediction that adjusts to scene changes. The system selectively applies different prediction modes and refinement levels based on motion activity, optimizing processing performance for varying content characteristics
3Device complexity
If conventional image encoding and decoding methods are used, then the processing is simpler, but the compression performance for 360-degree images is insufficient
Solution Approach 1:
The patent transforms the 360-degree image into multiple 2D projection faces (e.g., cube map projection) before applying conventional encoding techniques. This dimensional transformation allows standard compression algorithms to work effectively on spherical imagery while maintaining compression efficiency through face-wise independent processing
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.