Projection-Format 360-Degree Image Reconstruction for Compression Efficiency
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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 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, enhancing compression performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If 360-degree images are processed for virtual reality and augmented reality, then the amount of data generated increases massively, but the performance of image processing systems becomes insufficient
Solution Approach 1:
The patent divides the 360-degree image into multiple projection formats (e.g., equirectangular, cube map, octahedron, icosahedral) and processes each segment independently. This segmentation allows the system to handle the massive data by breaking it into manageable portions that can be encoded and decoded more efficiently, directly addressing the contradiction between data quantity and processing performance
2Ease of manufacture
If conventional image encoding methods are used for 360-degree images, then the encoding process is simple, but compression performance is insufficient for massive data
Solution Approach 1:
The patent creates a universal encoding framework that can handle multiple projection formats (equirectangular, cube map, octahedron, icosahedral) within a single system. This multi-functional approach maintains encoding simplicity while significantly improving compression performance by adapting to different 360-degree image representations, resolving the contradiction between process simplicity and compression efficiency
Data Source
AI summary
Disclosed are methods and apparatuses for image data encoding/decoding. A method for decoding a 360-degree image includes the steps of: receiving a bitstream obtained by encoding a 360-degree image; generating a prediction image by making reference to syntax information obtained from the received bitstream; adding the generated prediction image to a residual image obtained by dequantizing and inverse-transforming the bitstream, so as to obtain a decoded image; and reconstructing the decoded image into a 360-degree image according to a projection format. Therefore, the performance of image data compression can be improved.