Light Spot Location Algorithm for Aberrated Wavefronts
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Solution Overview
Problem
Existing optical measurement instruments, such as Shack-Hartmann wavefront sensors, face challenges in accurately locating valid light spots for highly aberrated wavefronts due to issues like focal spot crossover, irregular light spot locations, and interference from corneal reflex and tear film breakup, which affect measurement precision and data quality.
Innovation Solution
A method and system for determining valid light spots involve a two-stage process using a processor to select pixels based on intensity thresholds, validate light spot locations, and mask out adjacent pixels, employing algorithms like the Percent Threshold Method and Window Method to exclude invalid spots and account for aberrations, ensuring accurate light spot identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional light spot location methods are used for highly aberrated wavefronts, then measurement speed is maintained, but measurement precision deteriorates due to focal spot crossover and irregular light spot locations
Solution Approach 1:
The patent divides the light spot validation process into two distinct stages: a fast first stage that quickly identifies potential light spots using simple intensity thresholding, and a second stage that performs more rigorous validation on candidates from stage one. This segmentation allows the system to maintain high measurement speed while achieving high precision through the detailed validation in the second stage, resolving the contradiction between speed and precision.
Solution Approach 2:
The first stage performs preliminary filtering of pixels based on intensity thresholds before the more complex validation algorithms are applied in the second stage. This preliminary action eliminates obviously invalid pixels early, reducing the computational burden of subsequent precision validation and allowing the system to maintain both speed and accuracy.
2Measurement precision
If all detected light spots are used for measurement, then productivity is improved, but measurement precision deteriorates due to inclusion of invalid spots from corneal reflex and tear film breakup
Solution Approach 1:
The patent implements a feedback mechanism where light spots are validated against multiple criteria including intensity thresholds, spatial distribution patterns, and consistency checks. Invalid spots from corneal reflex or tear film breakup are detected through these feedback validations and excluded from measurements, ensuring high data quality without requiring manual review of each spot, thus maintaining productivity.
Solution Approach 2:
The validation algorithm automatically identifies and excludes invalid light spots without requiring external intervention. The system self-corrects by detecting patterns characteristic of invalid spots (such as those from corneal reflex or tear film breakup) and filtering them out, maintaining both high precision and productivity through automated quality control.
3Measurement precision
If intensity threshold filtering is applied to locate light spots, then measurement precision is improved by excluding invalid spots, but device complexity increases due to multiple validation stages
Solution Approach 1:
The validation process is segmented into two stages with increasing complexity. The first stage uses simple intensity threshold filtering that is computationally efficient. The second stage applies more complex validation algorithms only to the subset of candidates from stage one. This segmentation reduces the overall computational burden compared to applying complex algorithms to all pixels, while still achieving high precision.
Solution Approach 2:
The patent applies full validation rigor only partially - specifically, complex validation algorithms are applied only to candidate pixels that pass the first-stage intensity threshold. This partial application of excessive validation action ensures high precision for critical cases while avoiding the computational cost of applying the same rigorous validation to every pixel in the detector array.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances the accuracy of wavefront measurements by effectively filtering out invalid light spots and reducing errors caused by aberrations, leading to improved data quality and precision in optical measurements, particularly for highly aberrated wavefronts.
Implementation Method 1
optical detector 120 typically comprises a detector array or pixel array, for example, a charge-coupled device (CCD) camera or CMOS array
Implementation Method 2
lenslets of lenslet array 110 dissect an incoming wavefront and create a pattern of light spots 130 that fall onto optical detector 120
Data Source
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AI summary
An algorithm locates valid light spots produced on an image detector by a wavefront of interest. The algorithm includes sequentially examining pixels of the image detector to determine for each of the pixels whether the light intensity detected by the pixel is greater than a threshold, When the pixel's detected light intensity is determined to be greater than the threshold, the algorithm includes: determining whether the pixel belongs to a valid light spot; and when the pixel is determined to belong to a valid light spot; saving data indicating a location for the valid light spot; and masking out a group of pixels of the image detector at the determined location such that the masked pixels are considered to have a light intensity less than the threshold for a remainder of the sequential examination.