Projection-Aware 360-Degree Image Decoding for Compression Bottlenecks
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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, necessitating improved performance in image encoding and decoding.
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 based on projection formats like Equi-Rectangular, CubeMap, OctaHedron, and IcoSahedral Projection, with image expansion and motion vector prediction to enhance compression performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If multi-view images are captured and processed for 360-degree images, then the coverage and field of view are improved, but the amount of data generated increases massively
Solution Approach 1:
The 360-degree image data is divided into multiple view images captured by different cameras, allowing the large data volume to be processed in segmented units. Each view image can be encoded and transmitted separately, making the massive data more manageable while maintaining complete spherical coverage
Solution Approach 2:
The patent transforms the multi-view image data into equirectangular projection format, converting spatially distributed multi-camera data into a unified 2D spherical coordinate system. This dimensional transformation enables more efficient compression and processing while preserving the complete 360-degree field of view
2Measurement precision
If image processing systems process large amounts of data, then the quality and resolution are improved, but the processing performance becomes insufficient
Solution Approach 1:
The patent performs projection format conversion and equirectangular transformation during the encoding stage before transmission. By preprocessing the multi-view images into a standardized format with appropriate compression, the decoding device receives already-optimized data, significantly reducing the processing burden during playback while maintaining high image quality
Solution Approach 2:
The patent applies different quantization parameters and compression settings during the encoding process to optimize the balance between image quality and data size. By adjusting encoding parameters such as bitrate, resolution, and compression ratio, the system achieves high-quality output while improving processing efficiency
3Device complexity
If conventional encoding methods are used, then the system complexity is low, but the compression performance is insufficient for 360-degree images
Solution Approach 1:
The patent implements a universal encoding framework that handles multiple projection formats (equirectangular, cube map, octahedron, icosahedron) through a single encoding architecture. The system can adaptively select and process different projection types while maintaining consistent high compression performance, making the increased complexity worthwhile through its broad applicability and superior efficiency
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.