360-Degree Image Decoding With Syntax-Guided Prediction
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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, 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 specific projection formats like Equi-Rectangular, CubeMap, OctaHedron, and IcoSahedral, with image expansion based on partitioning units and adjacent pixel information.
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 processing large amounts of data generated by high-resolution multi-view images
Solution Approach 1:
The patent divides the 360-degree image processing into multiple views captured by separate cameras, with each view processed independently through its own encoding/decoding pipeline. This segmentation allows parallel processing of multiple image streams, significantly improving overall processing performance while managing the large data quantity generated by high-resolution multi-view imaging.
2Measurement precision
If high-resolution multi-view images are captured for 360-degree images, then the image quality is improved, but the amount of data generated increases massively
Solution Approach 1:
The patent combines multiple high-resolution view images into a unified 360-degree panoramic image through coordinate transformation and geometric stitching. By merging the separate view images into a single comprehensive representation, the system maintains high image quality across the entire 360-degree field of view while enabling more efficient storage and transmission compared to managing multiple separate high-resolution files.
3Ease of manufacture
If standard image encoding methods are used, then the implementation is straightforward, but the compression performance is insufficient for 360-degree images
Solution Approach 1:
The patent applies projection format parameters (such as equirectangular, cube map, or fisheye projections) to transform the 360-degree image into different geometric representations before encoding. This parameter change in the image structure allows standard compression algorithms to work more effectively on the transformed data, improving compression efficiency while maintaining implementation feasibility through well-established projection and encoding techniques.
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.