360-Degree Image Decoding with Recursive Block 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 various projection formats, including Equi-Rectangular, CubeMap, OctaHedron, and lcoSahedral, with image expansion based on partitioning units.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional image encoding/decoding methods are used for 360-degree images, then the processing can be performed with standard algorithms, but the performance is insufficient for the massive data generated by multi-view images
Solution Approach 1:
The patent divides the 360-degree image into multiple projection formats (Equi-Rectangular, CubeMap, OctaHedron, lcoSahedral) and processes each format separately with optimized algorithms. The image is also divided into partitioning units for parallel processing, which improves throughput for large datasets while maintaining manageable processing loads for each segment
Solution Approach 2:
The patent applies different processing parameters and algorithms specific to each projection format. By changing the processing approach based on the projection type (e.g., different expansion methods for CubeMap vs. ERP), the system optimizes performance for each format while handling large data volumes efficiently
2Manufacturing precision
If 360-degree images are processed with high resolution for virtual and augmented reality, then the image quality is improved, but the data amount increases massively
Solution Approach 1:
The patent applies different processing qualities and methods to different regions and projection formats based on their specific requirements. Each projection format receives optimized processing tailored to its characteristics, maintaining high quality where needed while reducing data where possible
Solution Approach 2:
By segmenting the 360-degree image into multiple projection formats and partitioning units, the system can apply selective quality levels and processing strategies to different segments, managing overall data volume while preserving necessary image quality for VR/AR applications
3Adaptability or versatility
If multiple projection formats are supported for 360-degree images, then the adaptability is improved, but the device complexity increases
Solution Approach 1:
The patent creates a universal processing framework that handles multiple projection formats (Equi-Rectangular, CubeMap, OctaHedron, lcoSahedral) through a common architecture. The system uses format-specific syntax information to route processing appropriately, providing multi-format support without requiring separate dedicated systems for each format
Solution Approach 2:
The system manages complexity by changing processing parameters based on the detected projection format. Rather than implementing fundamentally different processing pipelines for each format, the system uses format-specific parameters and algorithms within a unified framework, reducing overall system complexity while maintaining versatility
Data Source
AI summary
Disclosed are methods and apparatuses for decoding an image. A method includes receiving a bitstream obtained by encoding the image; dividing a first coding block into a plurality of second coding blocks; generating a prediction block of a second coding block based on syntax information obtained from the bitstream; and reconstructing the second coding block based on the prediction block and a residual block of the second coding block, the residual block being obtained by performing a dequantization and an inverse-transform on quantized transform coefficients from the bitstream. The first coding block has a recursive division structure. The first coding block is divided based on at least one of a quad tree division, a binary tree division or a triple tree division.