2D Whole-Image Reconstruction with Pixel-Based View Alignment
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Solution Overview
Problem
Existing methods for generating composite images from individual images captured with translational camera movement suffer from reduced image quality and distortions, particularly when the camera position changes relative to the object or recording area.
Innovation Solution
A method for generating a two-dimensional composite image by determining the spatial orientation of individual images based on pixel values and optimizing the relative alignment without additional aids, using a movable recording unit to capture sub-areas from different viewpoints and distances, and projecting these images onto a common image plane to form an overall image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If individual images are captured with translational camera movement to cover a large recording area, then the coverage area is improved, but image quality and resolution deteriorate due to position changes
Solution Approach 1:
The patent replaces mechanical alignment methods (physical markers, manual positioning) with a computational approach based on image data analysis. The system automatically determines spatial orientations by comparing pixel values and optimizing quality metrics, eliminating the need for mechanical reference systems and enabling high-precision alignment despite camera movement.
Solution Approach 2:
The patent changes the approach from assuming fixed camera position to actively optimizing spatial orientation parameters. By varying the relative spatial orientations as adjustable parameters and optimizing them based on pixel value comparisons, the system adapts to translational movement while maintaining image quality.
2Ease of manufacture
If traditional panorama stitching methods are used with spherical projection, then the processing is simplified, but distortions increase when camera position changes significantly
Solution Approach 1:
The patent replaces traditional spherical projection geometry with a computational optimization approach. Instead of forcing images onto a spherical surface, the system uses pixel value comparisons and quality metric optimization to determine appropriate spatial orientations, reducing geometric distortions while maintaining processing feasibility.
Solution Approach 2:
The patent introduces dynamic optimization of spatial orientations based on actual image content rather than static geometric assumptions. The relative spatial orientations are adjusted dynamically to maximize image quality metrics, allowing the system to adapt to varying camera positions and reduce distortions.
3Measurement precision
If additional aids like markers or structures are used for alignment, then alignment accuracy is improved, but device complexity increases
Solution Approach 1:
The patent enables the imaging system to align images using only the image data itself, without external markers or reference structures. The system extracts alignment information from the pixel values within the images, making the alignment process self-contained and eliminating additional hardware components.
Solution Approach 2:
The patent extracts alignment information directly from the pixel values of the images themselves, removing the need for separate marker systems. By utilizing the inherent information in the image data, the system achieves accurate alignment without adding external aids.
Data Source
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AI summary
The invention relates to a method for producing a two-dimensional whole image of a recording region, which is captured by means of a plurality of individual images each having its own viewing direction and its own distance, a spatial orientation of a main image plane of each individual image relative to a main image plane of the particular further individual image being determined on the basis of an overlap of the captured partial regions, and at least a plurality of individual images being combined in accordance with the spatial orientations to form the whole image. The whole image area is the surface of a torus.