Projection-Aware Recursive Blocks 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, necessitating improved performance in image encoding and decoding, particularly for high-resolution and high-quality images.
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 image in various projection formats, such as Equi-Rectangular, CubeMap, OctaHedron, and IcoSahedral, to enhance compression performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional image processing methods are used for 360-degree images, then image quality can be maintained, but the data volume and processing complexity increase massively
Solution Approach 1:
The patent divides the 360-degree image into multiple projection formats (Equi-Rectangular, CubeMap, OctaHedron, IcoSahedral) and processes each format separately. This segmentation allows the system to handle different types of 360-degree images with optimized methods for each format, reducing overall processing complexity and data volume while maintaining image quality.
Solution Approach 2:
The patent applies different encoding parameters and processing methods based on the projection format type. By changing parameters according to the specific projection format (e.g., using different block sizes, transformation methods, or quantization strategies for different formats), the system achieves efficient compression and processing tailored to each format's characteristics.
2Manufacturing precision
If high-resolution encoding is applied to 360-degree images, then image quality improves, but processing time and computational resources increase
Solution Approach 1:
The patent segments the high-resolution 360-degree image processing into multiple independent projection format handlers. Each format can be processed in parallel or independently optimized, reducing overall processing time while maintaining high resolution quality through format-specific optimizations.
Solution Approach 2:
The patent applies partial processing strategies where not all regions of the 360-degree image require the same level of processing. By identifying and processing only the most important regions at high resolution while using compressed representations for less critical areas, the system maintains perceived image quality while reducing total processing time and computational resources.
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.