Standalone Endoscope Objective Image Analysis by Focus Stitching
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Solution Overview
Problem
Evaluating the image quality of an endoscope objective is cumbersome and time-consuming due to its strong field curvature, requiring the entire optical system of the endoscope to be mounted during testing, which is costly and inefficient.
Innovation Solution
Capture a series of intermediate images with different focus areas along the optical axis, digitally stitch these images together using image processing and stitching algorithms to form a final image for evaluation, allowing the objective to be assessed independently of the endoscope's optical system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the entire optical system of the endoscope is mounted during testing, then the objective image quality can be evaluated, but the testing process becomes cumbersome, expensive and time consuming
Solution Approach 1:
The patent extracts and evaluates the objective lens independently from the complete endoscope optical system. By using a test chart positioned at the objective's image plane and capturing images directly with a camera, the evaluation process removes the need to mount the entire optical system, thereby reducing device complexity while maintaining measurement precision for the objective lens
Solution Approach 2:
The patent creates a digital copy of the objective image by capturing it with a camera and processing it through software algorithms. This digital replica allows for comprehensive image quality evaluation without requiring the physical presence of the complete optical system, reducing testing complexity while preserving evaluation accuracy
2Measurement precision
If the entire optical system of the endoscope is mounted during testing, then the objective image quality can be evaluated, but the testing process becomes time consuming
Solution Approach 1:
By extracting the objective lens evaluation from the complete endoscope system testing sequence, the patent enables standalone objective assessment. This eliminates the time required to assemble and align the entire optical system, reducing testing time while maintaining the ability to evaluate objective image quality through direct camera capture and software analysis
Solution Approach 2:
The patent employs preliminary focusing adjustments and image capture at multiple focal planes before final image reconstruction. By pre-positioning the test chart at the objective's image plane and capturing multiple focused images, the system prepares all necessary data for evaluation without requiring time-consuming post-processing or reassembly of the optical system
3Area of stationary object
If multiple intermediate images are captured and stitched, then the full image area can be evaluated, but the image processing complexity increases
Solution Approach 1:
The patent divides the image capture process into multiple segments, each capturing a different focal plane or region of the image. By capturing images at multiple focal positions and then stitching them together using software algorithms, the system achieves complete image area coverage while managing processing complexity through automated segmentation and reconstruction
Solution Approach 2:
The patent adds the focal plane dimension to the image capture process by capturing images at multiple focal depths. This dimensional expansion allows evaluation of the entire image area that would otherwise be out of focus, with software algorithms automatically stitching these multi-dimensional images into a complete evaluation dataset
Data Source
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AI summary
An objective of an endoscope can be evaluated by collecting a series of differently focused images and digitally stitching them together to obtain a final image for the endoscope that can be then evaluated. Movable optics and/or a camera can be used to collect the series of differently focused images. Image processing algorithms can be used to evaluate the collected images in terms of image sharpness and identify the areas at which each image is in relatively good focus. Once the areas of good focus are identified, the image processing algorithms can extract the areas of good focus. The digital stitching algorithms can be used to assemble the extracted areas of good focus to form a final image where most of the target scene should be in focus. The final image is then reviewed to determine the acceptability of the objective.