Projection-Aware 360-Degree Image Decoding for High Data Volumes
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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 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 and intra-prediction techniques to enhance compression performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional image encoding/decoding methods are used for 360-degree images, then the processing can be performed with standard algorithms, but the performance is insufficient for handling the massive data generated from multi-view images
Solution Approach 1:
The patent divides the 360-degree image processing into multiple projection formats (ERP, CMP, OHP, ISP) and processes different regions with different prediction modes. The image is segmented into face regions and non-face regions, with different intra-prediction modes applied to each segment, improving processing efficiency for the massive data volume
Solution Approach 2:
The patent applies different prediction modes to different regions of the 360-degree image based on local characteristics. Face regions use specific prediction modes while non-face regions use other modes, optimizing compression performance for each local area and improving overall processing performance
2Adaptability or versatility
If multiple projection formats are supported for 360-degree images, then the versatility and adaptability are improved, but the device complexity increases
Solution Approach 1:
The patent designs a universal decoding apparatus that can handle multiple projection formats (ERP, CMP, OHP, ISP) through a single integrated system. The syntax information parser automatically identifies the projection format from the bitstream and routes to the appropriate reconstruction module, providing multi-functionality without requiring separate dedicated systems for each format
3Loss of energy
If image expansion and intra-prediction techniques are applied, then the compression performance is enhanced, but the computational complexity increases
Solution Approach 1:
The patent performs image expansion on reference pictures before the prediction process. By pre-expanding the reference images to match the target resolution, the subsequent intra-prediction operations work with already-expanded data, improving compression efficiency while organizing the computational complexity in a structured sequence
Data Source
AI summary
A method for decoding a 360-degree image includes: 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; combining the generated prediction image with 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. Here, generating the prediction image includes: checking, from the syntax information, prediction mode accuracy for a current block to be decoded; determining whether the checked prediction mode accuracy corresponds to most probable mode (MPM) information obtained from the syntax information; and when the checked prediction mode accuracy does not correspond to the MPM information, reconfiguring the MPM information according to the prediction mode accuracy for the current block.