360-Degree Image Decoding with Projection-Format Reconstruction
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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 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 Equi-Rectangular, CubeMap, OctaHedron, and IcoSahedral, enhancing compression performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multi-view images are processed to generate 360-degree images for virtual reality and augmented reality, then the realism and immersion of media service are improved, but the amount of data generated increases massively
Solution Approach 1:
The patent divides the 360-degree image into multiple projection formats (e.g., equirectangular, cubemap, octahedron, icosahedral) and processes each segment separately. This segmentation allows the system to handle the massive data by breaking it into manageable portions that can be encoded and decoded more efficiently, reducing the overall data burden while maintaining the realism of the 360-degree view.
Solution Approach 2:
The patent transforms 360-degree spherical images into 2D plane projections through various projection formats. This dimensional transformation from 3D sphere to 2D plane enables more efficient data compression and processing, as 2D images are easier to handle with conventional encoding techniques compared to full 360-degree spherical data.
2Measurement precision
If the amount of data for 360-degree images increases massively, then the quality and detail of the image are improved, but the performance of image processing system deteriorates
Solution Approach 1:
By segmenting the 360-degree image into multiple projection formats and processing them separately, the system reduces the computational load on any single processing unit. This allows high-quality image processing to be maintained without overwhelming the system, as each segment can be processed in parallel or sequentially with manageable data sizes.
Solution Approach 2:
The patent changes the parameter of projection format to optimize processing performance. By selecting appropriate projection formats (equirectangular for simple views, cubemap for panoramic views, octahedron or icosahedral for complex geometries), the system adjusts the data structure to match the processing capabilities, thereby maintaining high image quality while improving processing speed.
3Device complexity
If conventional image encoding methods are used for 360-degree images, then the processing simplicity is maintained, but the compression performance is insufficient
Solution Approach 1:
The patent segments the 360-degree image into multiple projection formats that can be processed using conventional encoding methods. Each segment (equirectangular, cubemap, octahedron, or icosahedral) can be encoded independently using standard techniques, maintaining processing simplicity while improving overall compression performance through format-specific optimization.
Solution Approach 2:
By transforming the 360-degree image into 2D projections, the patent enables the use of conventional 2D encoding methods to process 360-degree content. This dimensional reduction maintains the simplicity of existing encoding infrastructure while achieving better compression performance, as 2D projections are more efficient to compress than full spherical data.
Data Source
AI summary
Disclosed are methods and apparatuses for image data encoding/decoding. A method for decoding a 360-degree image includes the steps of: receiving a bitstream obtained by encoding a 360-degree image; generating a prediction image by making reference to syntax information obtained from the received bitstream; adding the generated prediction image to a residual image obtained by dequantizing and inverse-transforming the bitstream, so as to obtain a decoded image; and reconstructing the decoded image into a 360-degree image according to a projection format. Therefore, the performance of image data compression can be improved.