360-Degree Image Reconstruction for Projection-Aware Compression
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Solution Overview
Problem
The existing image processing systems face challenges in efficiently handling the massive data generated for 360-degree images used in virtual and augmented reality, necessitating improved performance in image encoding and decoding methods.
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 a specific projection format, such as Equi-Rectangular, CubeMap, OctaHedron, or IcoSahedral, while optimizing compression performance through region-wise packing and image expansion based on partitioning units.
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 is 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 separately. 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 large data volume and processing performance.
Solution Approach 2:
The patent changes the projection format parameters to optimize compression performance. By adjusting parameters such as projection type, resolution, and bit depth for different regions or formats, the system achieves better compression ratios while maintaining processing speed, thus resolving the contradiction between data quantity and processing productivity.
2Ease of manufacture
If 360-degree images are encoded and decoded using conventional methods, then the image setting process is simple, but compression performance is insufficient
Solution Approach 1:
The patent applies different encoding parameters and compression techniques to different regions or projection formats of the 360-degree image. By optimizing compression locally for each projection format (e.g., using different quantization parameters for equirectangular vs. cube map), the system achieves better overall compression performance while maintaining ease of operation through automated parameter selection.
Solution Approach 2:
The patent dynamically adjusts encoding parameters based on the projection format and image content. The system automatically selects optimal compression settings for each projection type, making the process easy to operate while achieving superior compression performance. This dynamic adaptation resolves the contradiction between 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.