Block Division Decoding for 360-Degree Image Compression
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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 encoding and decoding methods.
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, or IcoSahedral, with image expansion based on partitioning units and motion information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If 360-degree images are captured and processed for virtual reality and augmented reality, then the visual quality and immersion experience are improved, but the amount of data generated increases massively
Solution Approach 1:
The 360-degree image is divided into multiple projection formats (ERP, CMP, OHP, ISP) and processed in segmented manner. The decoding process handles different projection formats separately, allowing efficient compression and processing of the massive data while maintaining visual quality across different viewing scenarios.
2Reliability
If the amount of data for 360-degree images increases massively, then the visual coverage and realism are improved, but the performance of the image processing system becomes insufficient
Solution Approach 1:
The patent performs image expansion and prediction operations before the main decoding process. By generating predicted images and performing expansion operations on reference pictures in advance, the system reduces the computational burden during real-time processing, thereby improving processing performance while maintaining full 360-degree visual coverage.
3Ease of manufacture
If conventional image encoding methods are used, then the implementation is simple, but the compression performance is insufficient for 360-degree images
Solution Approach 1:
The patent changes the processing parameters by introducing projection format-specific operations. Different projection formats (ERP, CMP, OHP, ISP) are handled with tailored expansion and prediction parameters, enabling efficient compression that adapts to the geometric characteristics of each format while maintaining implementation feasibility through standardized decoding frameworks.
Data Source
AI summary
Disclosed are methods and apparatuses for image data encoding/decoding. A method of decoding an image includes receiving a bitstream in which the image is encoded; obtaining index information for specifying a block division type of a current block in the image; and determining the block division type of the current block from a candidate group pre-defined in the decoding apparatus. The candidate group includes a plurality of candidate division types, including at least one of a non-division, a first quad-division, a second quad-division, a binary-division or a triple-division. The method also includes dividing the current block into a plurality of sub-blocks; and decoding each of the sub-blocks with reference to syntax information obtained from the bitstream.