Image Encoding and Decoding With Projection-Aware 360-Degree Partitioning
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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 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 based on partitioning units and reference pixels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If 360-degree images are captured with multiple cameras for virtual reality and augmented reality, then the realism and quality of the media service are improved, but the amount of data generated increases massively, overwhelming the processing capacity of existing image processing systems
Solution Approach 1:
The patent divides the 360-degree image into multiple projection formats (ERP, CMP, OHP, ISP) and processes different regions with different encoding strategies. The image is segmented into face regions, edge regions, and corner regions, each handled with appropriate compression techniques to balance quality and data reduction.
Solution Approach 2:
Different quality levels are applied to different regions of the 360-degree image. High-quality encoding is applied to face regions where visual importance is highest, while lower-quality encoding is applied to edge and corner regions, optimizing the balance between overall quality and data compression efficiency.
2Reliability
If high-resolution and high-quality images are processed for virtual reality and augmented reality, then the quality of the output image is improved, but the complexity of the encoding and decoding process increases
Solution Approach 1:
The patent performs preliminary conversion of the 360-degree image into multiple standard projection formats before the main encoding process. This preliminary action organizes the data in a structured manner that simplifies subsequent encoding and decoding operations, reducing overall process complexity while maintaining high output quality.
Solution Approach 2:
The patent utilizes multiple projection format parameters (ERP, CMP, OHP, ISP) to represent the same 360-degree image in different coordinate systems. By changing the representation parameters, the encoding process can select the most efficient format for different regions, simplifying the processing of high-resolution images.
3Productivity
If the amount of data for 360-degree images is reduced through compression, then the efficiency of the image processing system is improved, but the quality of the decoded image may deteriorate
Solution Approach 1:
The patent applies different compression ratios to different regions of the image. Face regions receive minimal compression (partial action) to preserve quality, while edge and corner regions undergo more aggressive compression. This selective approach maintains overall system efficiency while preserving critical image quality in important regions.
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.