Projection-Based 360-Degree Image Coding for Compression Efficiency
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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 high-resolution and high-quality 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, OHP, and ISP, while utilizing motion vector candidates and reference pictures for enhanced compression.
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 images
Solution Approach 1:
The 360-degree image is divided into multiple projection faces (e.g., cube faces in CMP format), allowing independent encoding and processing of each face. This segmentation enables better compression by treating each face as a separate encoding unit while maintaining overall image quality.
Solution Approach 2:
The patent transforms the 360-degree spherical image into multiple 2D projection planes (ERP, CMP, OHP, ISP formats). This dimensional transformation allows conventional 2D encoding techniques to be applied more effectively to the spherical data, improving compression performance.
2Manufacturing precision
If high-resolution 360-degree images are processed, then image quality is improved, but the data volume increases massively
Solution Approach 1:
Multiple projection faces are merged into a single bitstream with unified syntax structures. The encoder combines encoding results from multiple faces while sharing common parameters (e.g., motion vectors, prediction modes), reducing redundant data and lowering overall data volume.
Solution Approach 2:
The patent employs adaptive parameter selection for different projection formats, adjusting encoding parameters (block sizes, transformation types, quantization levels) based on the specific projection format and image characteristics, thereby optimizing compression for high-resolution data.
3Adaptability or versatility
If multiple projection formats are supported, then versatility is improved, but system complexity increases
Solution Approach 1:
The encoder is designed with a universal syntax structure that can handle multiple projection formats (ERP, CMP, OHP, ISP) through a common framework. Format-specific parameters are optional and only activated when needed, allowing the system to support multiple formats without requiring separate encoding paths for each.
Solution Approach 2:
The system dynamically selects and configures encoding parameters based on the chosen projection format. The syntax elements are adaptively enabled or disabled according to the active format, allowing the encoder to maintain high versatility while managing complexity through dynamic parameter configuration rather than static multi-format support.
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.