360-Degree Image Reconstruction for Projection-Based Compression
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Solution Overview
Problem
The existing image processing systems face challenges in efficiently handling the massive data generated by 360-degree images for 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 involves 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 considering 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 becomes insufficient
Solution Approach 1:
The patent divides the 360-degree image into multiple equirectangular images by partitioning the spherical coordinate system into multiple zones (e.g., vertical zones, horizontal zones). Each zone is independently encoded and processed, reducing the data processing burden on the system while maintaining the complete 360-degree coverage. This segmentation allows parallel processing and reduces the computational complexity per unit.
Solution Approach 2:
The patent transforms the 360-degree spherical image data into a 2D equirectangular projection format, converting three-dimensional spherical coordinates to two-dimensional rectangular coordinates. This dimensional transformation enables the use of efficient 2D image processing algorithms and compression techniques, significantly improving processing performance while preserving the 360-degree spatial information.
2Loss of energy
If 360-degree images are encoded and decoded, then compression performance is enhanced, but the complexity of the encoding and decoding process increases
Solution Approach 1:
The patent segments the 360-degree image into multiple equirectangular images corresponding to different spherical zones. Each segment is independently encoded using standard image coding tools, allowing the use of well-established, computationally efficient algorithms. This segmentation reduces the complexity of handling the entire 360-degree image as a single unit while achieving effective compression through zone-based processing.
Solution Approach 2:
The patent employs a universal equirectangular projection framework that can handle various 360-degree image types and applications. The same encoding and decoding processes applied to each equirectangular zone can be used across different scenarios (virtual reality, augmented reality, panoramic imaging), reducing the need for specialized complex algorithms for each specific application case.
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.