Recursive Block Image Decoding for 360-Degree Projection Compression
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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 high-resolution and high-quality 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 specific projection formats like Equi-Rectangular, CubeMap, OctaHedron, or IcoSahedral, enhancing compression performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If 360-degree images are captured with multiple cameras for virtual reality and augmented reality, then image quality and resolution are improved, but the amount of data generated increases massively
Solution Approach 1:
The patent divides the 360-degree image into multiple projection formats (Equi-Rectangular, CubeMap, OctaHedron, IcoSahedral) and processes each format separately through dedicated decoding paths. This segmentation allows the system to handle different projection types independently, improving processing efficiency while maintaining high image quality across all formats without being overwhelmed by the total data volume.
Solution Approach 2:
The patent transforms the massive 360-degree image data from a single complex representation into multiple dimensional projection formats. By converting the spherical 360-degree data into various geometric projections (cube, octahedron, icosahedron), the system creates multiple dimensional representations that are more manageable for processing and storage, effectively reducing the complexity of handling the original massive data set.
2Manufacturing precision
If high-resolution and high-quality images are processed, then image quality is improved, but the performance of the image processing system becomes insufficient
Solution Approach 1:
The patent segments the image processing task into distinct decoding paths for different projection formats (Equi-Rectangular, CubeMap, OctaHedron, IcoSahedral). Each projection format has its own dedicated decoding process, allowing parallel processing of multiple image types simultaneously. This segmentation enables the system to maintain high image quality for each format while improving overall processing throughput and system performance.
3Device complexity
If conventional image encoding and decoding methods are used, then processing simplicity is maintained, but compression performance is insufficient for 360-degree images
Solution Approach 1:
The patent applies dimensionality change by transforming 360-degree spherical image data into multiple geometric projection formats (cube, octahedron, icosahedron, rectangular). This transformation enables the use of conventional 2D image encoding and decoding techniques on each projected format, maintaining processing simplicity while dramatically improving compression performance. The multi-dimensional projection approach allows standard compression algorithms to work effectively on what would otherwise require complex spherical coordinate transformations.
Data Source
AI summary
Disclosed are methods and apparatuses for decoding an image. A method includes receiving a bitstream obtained by encoding the image; dividing a first coding block into a plurality of second coding blocks; generating a prediction block of a second coding block based on syntax information obtained from the bitstream; and reconstructing the second coding block based on the prediction block and a residual block of the second coding block, the residual block being obtained by performing a dequantization and an inverse-transform on quantized transform coefficients from the bitstream. The first coding block has a recursive division structure. The first coding block is divided based on at least one of a quad tree division, a binary tree division or a triple tree division.