Tree-Structured Block Division for 360-Degree Image Compression
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Solution Overview
Problem
Existing image processing systems struggle with the massive data generated by 360-degree images for virtual and augmented reality, necessitating improved performance in image encoding and decoding methods.
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 decoded image based on projection formats like ERP, CMP, OHP, and ISP, with image expansion performed on partitioning units using adjacent pixel information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If 360-degree images are processed using conventional image encoding methods, then the images can be captured and stored, but the data amount becomes excessively large and processing performance is insufficient
Solution Approach 1:
The patent divides the 360-degree image into multiple partitioning units (e.g., cubemap faces, spherical regions) that can be processed independently. Each partitioning unit is encoded separately using syntax information and residual images, allowing parallel processing and reducing the computational burden on single large-image processing systems.
2Loss of information
If image encoding complexity is increased to improve compression performance, then compression ratio improves, but processing time and system requirements increase
Solution Approach 1:
The patent applies different encoding strategies to different partitioning units based on their local characteristics. Syntax information is generated specifically for each partitioning unit's boundaries and relationships, allowing optimized compression for each region while maintaining overall image quality. This localized approach improves compression without uniformly increasing complexity across the entire system.
3Ease of manufacture
If conventional block division methods are used for 360-degree images, then encoding can be performed, but the unique characteristics of 360-degree images are not considered leading to suboptimal compression
Solution Approach 1:
The patent transitions from conventional 2D block division to 3D-spatial-aware partitioning suitable for 360-degree images. Partitioning units are defined based on spherical or cubemap geometry, and syntax information captures spatial relationships in three dimensions. This dimensional adaptation enables more efficient compression by respecting the intrinsic 360-degree image structure rather than forcing it into traditional 2D encoding 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.