Hierarchical Image Data Creation with Quadtree Metadata
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Solution Overview
Problem
The complexity of creating image data with hierarchical structures for display systems increases the burden on users, requiring additional expertise and effort, especially when dealing with high-definition images and varying zoom factors.
Innovation Solution
An image processing system that supports the creation of hierarchical image data by allowing users to easily switch between different layers of resolution and zoom factors, using a quadtree structure and metadata to align and interpolate images, reducing the need for extensive manual alignment and effort.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If hierarchical image data structure is used for efficient display scaling, then image display efficiency is improved, but content creation complexity increases
Solution Approach 1:
The system automatically generates the hierarchical image data structure from a single input image without requiring manual user intervention. The image processing device performs multi-resolution analysis and tile generation autonomously, converting the complex creation process into a self-service operation that maintains display efficiency while eliminating manual complexity
Solution Approach 2:
The hierarchical image data structure is pre-generated and stored before actual display needs arise. By performing the complex image processing operations in advance and organizing images into a ready-to-use hierarchical format with metadata, the system eliminates the need for complex real-time processing during display operations
2Manufacturing precision
If manual alignment and creation of hierarchical image data is performed, then image precision is improved, but user burden increases
Solution Approach 1:
The system replaces manual mechanical alignment operations with automated image processing algorithms. The image processing device uses computational methods to perform multi-resolution analysis, automatic tile generation, and precise alignment based on metadata, substituting user manual work with automated processing that achieves equal or superior precision
Solution Approach 2:
Metadata acts as an intermediary that automatically carries alignment and positioning information between different resolution layers. Instead of requiring users to manually align images, the system generates metadata that automatically encodes the spatial relationships and alignment data, enabling precise image hierarchy construction without user intervention
Data Source
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AI summary
A user performs input to select a capture mode (S10). Then the user captures an image at a desired zoom magnification as a target image (S12). An image capture device determines zoom magnifications of an image to be captured with the target image as an origin, and captures images while zooming out to the determined zoom magnifications (S14, S16). Changes of the zoom magnifications and processing of image captures are repeated until the minimum zoom magnification of the determined zoom magnifications is reached (N of S18, S14, and S16), and upon completing capture of the image at the minimum zoom magnification (Y of S18), metadata which includes the zoom magnification and relative position information of the image for each image is created, associated with data of the captured images, and stored in the storage unit (S20).