360-Degree Image Decoding With Adaptive MPM Reconfiguration
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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 it into the 360-degree format, utilizing projection formats like Equi-Rectangular, CubeMap, OctaHedron, and IcoSahedral, 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 volume generated by 360-degree images
Solution Approach 1:
The patent applies segmentation by dividing the 360-degree image into multiple projection formats (Equi-Rectangular, CubeMap, OctaHedron, IcoSahedral) and processing them separately. The decoding apparatus reconstructs the decoded image into different projection formats based on syntax information, allowing parallel processing and optimization for each format's specific characteristics, thereby improving overall processing performance for large data volumes
Solution Approach 2:
The patent transforms the 360-degree image data from a single complex representation into multiple dimensional projections. By converting the spherical 360-degree image into various 2D projection formats (cube, octahedron, icosahedron, equi-rectangular), the system enables more efficient encoding and decoding operations in lower dimensions while preserving the original spatial relationships and visual quality
2Measurement precision
If image expansion is performed on the reference picture to generate predicted images, then the prediction accuracy improves, but the computational complexity increases
Solution Approach 1:
The patent applies preliminary action by performing image expansion on the reference picture before generating predicted images. The decoding apparatus expands the reference picture in advance to match the current block's dimensions, then uses this pre-expanded reference for intra-prediction. This preliminary expansion ensures that all necessary reference pixels are available, improving prediction accuracy while organizing the computational workload in a structured manner
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.