360-Degree Image Decoding with Projection Format Reconstruction
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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 decoding 360-degree images 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 enhancing compression performance through image expansion and rearrangement based on partitioning units.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If 360-degree images are processed for virtual reality and augmented reality, then the quality and realism of media service is improved, but the amount of data generated increases massively
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, reducing the overall data volume while maintaining quality.
Solution Approach 2:
The patent changes the projection format parameters to optimize data compression. By transforming the 360-degree image into different projection formats with specific geometric parameters, the system can reduce data redundancy and improve compression efficiency, thereby reducing the quantity of data while preserving media service quality.
2Quantity of substance
If the amount of data for 360-degree images is processed, then comprehensive image information is obtained, but the performance of image processing system becomes insufficient
Solution Approach 1:
The patent segments the image processing task into multiple projection format conversions and encoding operations. By processing the 360-degree image in segments (different projection formats), the system can handle large data volumes more efficiently and improve processing performance through parallelization and optimized algorithms for each segment.
Solution Approach 2:
The patent transforms the 2D 360-degree image into different dimensional representations through various projection formats (cube map, octahedron, icosahedral). This dimensional transformation allows the system to process and compress the image data more efficiently, improving processing performance while maintaining comprehensive image information.
3Loss of energy
If image encoding and decoding is performed on 360-degree images, then compression is achieved, but the complexity of the encoding/decoding process increases
Solution Approach 1:
The patent segments the encoding/decoding process into separate modules for different projection formats. Each projection format (equirectangular, cube map, octahedron, icosahedral) has its own dedicated encoding and decoding algorithms, which simplifies the overall process by making each individual module more manageable and optimized, while achieving compression efficiency through the combined output of all segments.
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.