360-Degree Image Encoding with Region-Based Compression Control
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Solution Overview
Problem
Existing image processing systems face challenges in efficiently handling and processing large amounts of data generated by 360-degree images for virtual and augmented reality, particularly in terms of performance improvement in encoding and decoding processes.
Innovation Solution
A method and apparatus for encoding and decoding 360-degree images that utilize layer-based partitioning, resizing, and projection format conversion to enhance compression performance, including tree-based block partitioning and inter-prediction techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If 360-degree images are processed using conventional image encoding methods, then the encoding process can be performed with standard algorithms, but the compression performance is insufficient and processing efficiency is low
Solution Approach 1:
The patent divides the 360-degree image into multiple regions based on projection formats (e.g., equirectangular, cubic, spherical). Different encoding parameters and techniques are applied to each region according to its specific characteristics, enabling optimized compression while maintaining processing efficiency.
Solution Approach 2:
The patent applies different encoding quality levels and compression parameters to different regions of the 360-degree image. High-importance regions (such as front-view areas) are encoded with higher quality, while less important regions use lower quality settings, thereby improving overall compression performance without uniformly sacrificing image quality.
2Manufacturing precision
If the amount of data for 360-degree images is increased to maintain high resolution and quality, then image quality is improved, but the performance of the image processing system becomes insufficient
Solution Approach 1:
The patent dynamically adjusts encoding parameters such as quantization step size, transformation block size, and prediction mode based on the importance of different regions in the 360-degree image. This allows the system to maintain high image quality in critical areas while reducing data volume in less important areas, thereby improving system processing performance.
Solution Approach 2:
The patent applies full-resolution encoding only to essential regions (such as the front view in VR applications), while using reduced resolution or lower quality encoding for peripheral regions. This partial application of high-quality encoding maintains necessary image quality while significantly reducing the total data volume and improving system performance.
Data Source
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AI summary
Disclosed is an image data encoding/decoding method and apparatus. A method for decoding a 360-degree image comprises 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; combining the generated prediction image with 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. Here, the step of generating the prediction image comprises the steps of: obtaining, from motion information included in the syntax information, a motion vector candidate group including a motion vector of a block adjacent to a current block to be decoded; deriving a prediction motion vector from the motion vector candidate group, on the basis of selection information extracted from the motion information; and determining a prediction block for the current block to be decoded, using a fmal motion vector derived by adding the prediction motion vector to a differential motion vector extracted from the motion information.