Tree-Based Block Partitioning for 360-Degree Image Decoding
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Solution Overview
Problem
Existing image processing systems struggle with the massive data generated by 360-degree images for virtual and augmented reality, requiring improved performance in image encoding and decoding.
Innovation Solution
A method for encoding and decoding 360-degree images that includes generating a predicted image using syntax information, combining it with a residual image, and reconstructing the image based on projection formats like ERP, CMP, OHP, and ISP, with image expansion and rearrangement of blocks to enhance 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 image quality and realism are improved, but the amount of data generated increases massively
Solution Approach 1:
The patent divides the 360-degree image into multiple blocks and further subdivides them into prediction blocks and residual blocks. This segmentation allows independent processing of different image regions, enabling efficient compression while maintaining overall image quality. The block-based division facilitates selective application of different encoding strategies to different parts of the image.
Solution Approach 2:
The patent extracts the residual information (difference between original and predicted blocks) separately from the prediction blocks. By taking out only the essential residual data that needs to be transmitted, the system reduces the overall data volume while preserving image quality. The residual blocks contain only the necessary information to reconstruct the original image from predictions.
2Productivity
If the image is divided into blocks and further divided into prediction blocks and residual blocks, then compression performance is improved, but the processing complexity increases
Solution Approach 1:
The patent segments the image processing into distinct stages: block division, prediction block generation, residual block calculation, and separate encoding of both components. This segmentation allows each stage to be optimized independently, improving overall compression performance while making the complex process more manageable through modular processing.
Solution Approach 2:
The patent performs prediction block generation before final encoding. By preliminarily creating prediction blocks that approximate the original image content, the system reduces the amount of data that needs to be encoded and transmitted. This preliminary action simplifies the subsequent encoding process by working with smaller residual differences rather than complete image data.
3Productivity
If tree structure-based block division is used for encoding and decoding, then the efficiency of handling large data volumes is improved, but the initial image setting process becomes more complex
Solution Approach 1:
The patent implements a tree structure-based block division system that recursively divides the image into progressively smaller blocks. This hierarchical segmentation allows efficient data handling by organizing image data in a structured manner that facilitates both compression and rapid access. The tree structure enables systematic processing of large data volumes through divide-and-conquer methodology.
Solution Approach 2:
The patent employs dynamic block division where the size and structure of blocks can vary based on image content characteristics. The tree structure allows adaptive refinement of block sizes in different regions of the image, enabling more efficient compression for complex regions while maintaining speed for simpler areas. This dynamic approach optimizes the balance between processing efficiency and compression performance.
Data Source
AI summary
Disclosed are methods and apparatuses for image data encoding/decoding. A method of decoding an image includes receiving a bitstream in which the image is encoded; obtaining index information for specifying a block division type of a current block in the image; and determining the block division type of the current block from a candidate group pre-defined in the decoding apparatus. The candidate group includes a plurality of candidate division types, including at least one of a non-division, a first quad-division, a second quad-division, a binary-division or a triple-division. The method also includes dividing the current block into a plurality of sub-blocks; and decoding each of the sub-blocks with reference to syntax information obtained from the bitstream.