360-Degree Image Reconstruction Using Projection-Format Prediction
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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, requiring improved performance in image encoding and decoding, particularly for 360-degree 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 lcoSahedral, enhancing compression performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If 360-degree images are processed for virtual reality and augmented reality, then the quality and realism of media service is 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, cube map, octahedron) 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 quality.
Solution Approach 2:
The patent changes the parameter of projection format to optimize data processing. By transforming the 360-degree image into different projection formats with varying data characteristics, the system can select the most efficient format for encoding and decoding, thereby reducing the amount of data while preserving the quality and realism of the media service.
2Loss of energy
If the amount of data for 360-degree images is processed, then the compression performance is improved, but the performance of image processing system becomes insufficient
Solution Approach 1:
The patent segments the image processing task into multiple projection format conversions and encoding operations. By processing the 360-degree image in segments (e.g., converting to different projection formats separately), the system can improve compression performance while maintaining adequate processing speed through parallel or sequential handling of segments.
Solution Approach 2:
The patent optimizes processing parameters by selecting appropriate projection formats and encoding settings based on the specific requirements of the media service. This parameter optimization enables better compression performance without overwhelming the image processing system, balancing data reduction with processing capability.
3Loss of energy
If image encoding and decoding is performed on 360-degree images, then the compression performance is improved, but the complexity of the encoding and decoding process increases
Solution Approach 1:
The patent segments the encoding and decoding process into distinct stages: converting the 360-degree image to different projection formats, encoding each format separately, and then decoding and reconstructing the image. This segmentation simplifies the overall process by breaking down complex operations into manageable steps that can be handled by standard encoding tools.
Solution Approach 2:
The patent employs universal projection format conversion techniques that can be applied across different encoding scenarios. By using multi-functional projection formats (e.g., equirectangular, cube map, octahedron) that support various encoding standards, the system achieves good compression performance without requiring entirely new complex encoding algorithms, thus reducing the increase in process complexity.
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.