Curved Surface Image Reconstruction Using Curvilinear Coordinates
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Solution Overview
Problem
Existing technologies face challenges in generating accurate curved surface images from three-dimensional data, particularly when dealing with targets that have uneven or curved surfaces, leading to distortions and reduced image accuracy due to wobble during optical coherence tomography.
Innovation Solution
An information processing apparatus and method that calculates curvilinear coordinates based on curvature information, allowing the generation of a curved surface image by incorporating both first and second positions on the target's surface, even when the initial measurement positions are irregular.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional image reconstruction methods are used for curved surfaces, then processing accuracy is maintained, but processing load and time increase significantly
Solution Approach 1:
The patent performs preliminary calculation of curvilinear coordinates and curvature information before actual image reconstruction. By pre-processing the coordinate transformation and curvature data, the system reduces the computational burden during the main reconstruction phase, enabling faster processing while maintaining accuracy for curved surface imaging
Solution Approach 2:
The patent transforms the imaging problem from Cartesian coordinates to curvilinear coordinates that adapt to the curved surface geometry. This parameter transformation allows the reconstruction algorithm to work with coordinates that naturally follow the surface curvature, improving both efficiency and accuracy without requiring computationally intensive conventional methods
2Ease of manufacture
If regular grid sampling is used for three-dimensional data acquisition, then data collection is simplified, but image accuracy deteriorates due to wobble and curved surface distortions
Solution Approach 1:
The patent applies curvilinear coordinate transformation that conforms to the curved surface geometry of the target object. Instead of forcing regular grid sampling onto a curved surface, the system transforms the irregularly sampled data into curvilinear coordinates that naturally accommodate the surface curvature, thereby maintaining image accuracy while keeping data acquisition relatively simple
Solution Approach 2:
The patent introduces curvilinear coordinates as an intermediary transformation layer between the irregularly sampled three-dimensional data and the final two-dimensional surface image. This intermediate coordinate system acts as a mediator that reconciles the simplicity of regular sampling with the accuracy requirements of curved surface imaging by warping the coordinate space to match the surface geometry
3Measurement precision
If high-resolution data is collected from all positions on the curved surface, then image quality is maximized, but data collection time and processing complexity increase
Solution Approach 1:
The patent employs compressive sensing techniques that allow accurate reconstruction of high-resolution images from a reduced set of measurements. By collecting data from fewer positions than traditionally required and using the curvilinear coordinate transformation along with sparsity constraints, the system can reconstruct high-quality images with less data, thereby reducing data collection time while maintaining or even improving image quality
Solution Approach 2:
The patent reconstructs the complete high-resolution surface image by computationally inferring missing information from the partially sampled data. Using the curvilinear coordinate system and compressive sensing algorithms, the system creates a virtual copy of the full-resolution data that would be obtained from complete sampling, but achieves this with significantly fewer measurements, reducing data collection time while preserving image quality
Data Source
AI summary
An information processing method comprising: acquiring three-dimensional data on a target; calculating curvature information indicating a curvature of a surface of the target, on the basis of the three-dimensional data; calculating curvilinear coordinates of a plurality of first positions on the surface of the target, on the basis of the curvature information; calculating curvilinear coordinates of a plurality of second positions on the surface of the target, which are different from the plurality of first positions, on the basis of the curvature information and the curvilinear coordinates of the plurality of first positions; and generating a curved surface image indicating the surface of the target, on the basis of the curvilinear coordinates of the plurality of first positions and the curvilinear coordinates of the plurality of second positions.