Edge Response Data Processing for Electro-Optical MTF Measurement
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Solution Overview
Problem
Conventional methods for calculating the modulation transfer function (MTF) of electro-optical systems using knife-edge targets suffer from poor quantitative accuracy, loss of phase information, and reproducibility issues, especially beyond the Nyquist frequency, due to smoothing and data manipulation errors.
Innovation Solution
A method that involves obtaining edge response data from a knife-edge target, constructing line slopes to minimize data spread, and using least squares regression to calculate the MTF, while preserving phase information and centering data points to improve accuracy and reproducibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional smoothing methods are applied to remove noise from edge response data, then noise is reduced, but meaningful information is lost and apparent information is introduced
Solution Approach 1:
The patent extracts only the essential information needed for MTF calculation by using a minimum spanning tree to connect edge response data points. This selective extraction removes noise while preserving the true signal by only connecting points that represent actual edge transitions, rather than applying blanket smoothing that removes all variations including meaningful ones.
Solution Approach 2:
Instead of smoothing the data to remove noise (conventional approach), the patent inverts the approach by using a minimum spanning tree to selectively connect only the necessary data points. This inverted methodology preserves meaningful information while filtering out noise by requiring direct line-of-sight connections between points.
2Object-affected harmful factors
If arbitrary smoothing of image data is applied to remove noise, then noise is reduced, but quantitative accuracy of MTF deteriorates
Solution Approach 1:
The patent extracts only the essential edge response information needed for accurate MTF calculation by using a minimum spanning tree. This selective extraction process removes noise while preserving the true signal characteristics, maintaining quantitative accuracy even at high spatial frequencies where conventional smoothing fails.
Solution Approach 2:
The patent changes the fundamental parameter from continuous smoothing to discrete point-by-point connection using a minimum spanning tree. This parameter change allows the system to maintain quantitative accuracy by only connecting points that represent true edge transitions, rather than applying arbitrary smoothing that degrades accuracy.
3Device complexity
If phase information is ignored to simplify MTF calculation, then calculation complexity is reduced, but accuracy at spatial frequencies above Nyquist deteriorates
Solution Approach 1:
The patent segments the MTF calculation into two distinct parts: MTF magnitude calculation (which can be done without phase information) and OTF phase calculation (which preserves phase information). This segmentation allows users to choose the appropriate level of complexity based on their needs, while maintaining the option to preserve phase information for accurate results above Nyquist frequency.
Solution Approach 2:
The patent makes the calculation approach dynamic by providing two options: a simplified MTF calculation that ignores phase information for basic applications, and a more comprehensive OTF calculation that preserves phase information for high-precision applications above Nyquist frequency. This dynamic approach allows the system to adapt to different accuracy requirements.
4Ease of manufacture
If data manipulation and smoothing are applied to calculate MTF, then calculation can be performed, but reproducibility deteriorates
Solution Approach 1:
The patent extracts the essential edge response data using a minimum spanning tree that connects points based on their spatial relationships rather than arbitrary smoothing parameters. This extraction method is deterministic and reproducible because it relies on the geometric relationships between data points rather than subjective smoothing choices.
Solution Approach 2:
The patent creates a simplified copy of the edge response data by representing it as a minimum spanning tree structure. This copy preserves the essential geometric relationships and edge transitions while eliminating the need for complex smoothing operations, making the calculation reproducible across different systems and operators.
Data Source
AI summary
A method for obtaining a modulation transfer function (MTF) of a knife-edge target imaged by an electro-optical device is described. The method includes the steps of: (a) obtaining edge response data points, where a data point includes a perpendicular distance, d, to the knife-edge target; and (b) constructing a sequence of line slopes of the edge response data points, where a line slope includes a spread of edge response data points. The method then selects a line slope that minimizes the spread of edge response data points, and calculates the MTF, based on the edge response data points included in the selected line slope. The MTF is provided to a user. An edge response data point is defined by a pair of values of (d, E) of a pixel, where distance, d, is the shortest distance between the pixel and a line slope and the pixel has an intensity value, E.