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 from multi-view images for 360-degree images in virtual and augmented reality, leading to insufficient performance in encoding and decoding high-resolution 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 various projection formats, utilizing image expansion and intra-prediction techniques to enhance compression performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multi-view images are captured and processed for 360-degree images, then the realism and quality of virtual reality and augmented reality services are improved, but the amount of data generated increases massively and the performance of image processing systems becomes insufficient
Solution Approach 1:
The 360-degree image is divided into multiple projection formats (ERP, CMP, OHP, ISP) that can be independently processed. The encoding apparatus segments the image data according to different projection formats, allowing parallel processing and reducing the overall processing time while maintaining high quality for each format
Solution Approach 2:
The patent transforms the 360-degree image data into multiple dimensional projection formats (2D ERP, cubic CMP, octahedral OHP, polyhedral ISP). This dimensional transformation allows the same image data to be processed and transmitted in different geometric representations, improving processing efficiency without sacrificing quality
2Reliability
If high-resolution images are encoded and decoded, then the image quality is improved, but the compression performance and processing efficiency deteriorate
Solution Approach 1:
The patent applies different encoding strategies to different regions and projection formats based on their specific characteristics. Each projection format (ERP, CMP, OHP, ISP) receives optimized encoding parameters suited to its geometric properties, achieving high quality with improved compression efficiency by avoiding uniform over-processing
Solution Approach 2:
The encoding apparatus dynamically adjusts encoding parameters such as quantization levels, transformation blocks, and prediction modes based on the specific projection format and image content. This parameter optimization maintains high image quality while significantly improving compression performance compared to fixed-parameter encoding
3Loss of information
If image processing systems process large amounts of data, then the completeness of information is improved, but the system performance becomes insufficient
Solution Approach 1:
The patent performs preliminary organization and classification of image data according to multiple projection formats before the main encoding process. By pre-structuring the data in a standardized multi-format framework, the system reduces the complexity of subsequent processing operations while ensuring no information is lost in the transformation process
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.