Image Block Partition Decoding for 360-Degree 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, 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 the image in a specific projection format, utilizing image expansion based on partitioning units and motion information to enhance compression performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional image encoding methods are used for 360-degree images, then the encoding process is simple, but the compression performance is insufficient for massive data volumes
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 prediction and transformation methods to optimize compression while managing complexity.
Solution Approach 2:
The patent transforms the 360-degree image from spherical coordinates to multiple 2D projection formats. This dimensional transformation allows conventional 2D encoding techniques to be applied effectively to 360-degree content, improving compression performance without requiring entirely new encoding architectures.
2Manufacturing precision
If image processing is performed on full-resolution 360-degree images, then image quality is maintained, but the data volume becomes unmanageable for current systems
Solution Approach 1:
The patent applies different quality levels and encoding parameters to different regions of the 360-degree image. Important regions such as face centers receive higher quality encoding, while less critical regions like edges and corners use more aggressive compression, optimizing the balance between overall image quality and data volume reduction.
Solution Approach 2:
The patent processes only the most critical regions of the 360-degree image at full quality, while applying reduced processing to less important areas. This partial action approach maintains acceptable image quality for key regions while significantly reducing the total data volume that current systems must handle.
3Adaptability or versatility
If multiple projection formats are supported for 360-degree images, then versatility is improved, but the processing complexity increases
Solution Approach 1:
The patent designs an encoding system that can handle multiple projection formats (ERP, CMP, OHP, ISP) using a unified processing framework. The same basic encoding architecture is adapted to work with different projection types, allowing the system to support multiple formats without requiring entirely separate processing pipelines for each format.
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.