360-Degree Image Reconstruction Across Projection Formats
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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 according to projection formats like Equi-Rectangular, CubeMap, OctaHedron, and IcoSahedral, enhancing compression performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If 360-degree images are captured with multiple cameras for virtual reality and augmented reality, then the realism and immersive experience are 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, cubemap, octahedron, icosahedral) and processes each format separately. This segmentation allows the system to handle the massive data by breaking it down into manageable components that can be encoded and decoded more efficiently, reducing the overall data burden while maintaining the 360-degree viewing experience.
Solution Approach 2:
The patent transforms 360-degree images from a spherical/3D representation into various 2D projection formats. This dimensional transformation enables the system to process and transmit image data more efficiently by converting complex 3D data into flatter, more compressible 2D representations, thereby reducing data quantity while preserving the essential visual information for immersive experiences.
2Measurement precision
If the amount of image data is increased for 360-degree processing, then the quality and detail of the image are improved, but the performance of the image processing system becomes insufficient
Solution Approach 1:
The patent applies different processing techniques and projection formats to different regions or aspects of the 360-degree image. By tailoring the processing method to the specific characteristics of each region (e.g., using cubemap for certain areas and equirectangular for others), the system maintains high image quality while optimizing processing performance for each local region, avoiding the need to process the entire massive dataset with the same intensive method.
Solution Approach 2:
The patent changes the parameter representation of the image data by converting between different projection formats. This parameter transformation allows the system to adjust the data representation to match the processing capabilities and performance requirements of the system, enabling efficient processing of high-quality 360-degree images by selecting appropriate projection parameters for each processing stage.
3Ease of operation
If image encoding and decoding methods are used for 360-degree images, then the data transmission is enabled, but the compression performance is insufficient
Solution Approach 1:
The patent implements a universal image encoding system that can handle multiple projection formats (equirectangular, cubemap, octahedron, icosahedral) within a single encoding framework. This multi-functional approach allows the system to transmit 360-degree images efficiently by using a unified encoding method that adapts to different projection types, improving compression performance while maintaining ease of data transmission across various formats.
Solution Approach 2:
The patent performs preliminary processing by converting the 360-degree image into different projection formats before encoding. This preliminary action prepares the data in a more compression-friendly format, enabling more efficient compression during the encoding process. By pre-transforming the image data into optimized representations, the system achieves better compression efficiency without complicating the subsequent transmission process.
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.