This Python-based Modulation Transfer Function (MTF) calculator offers a cost-effective alternative to MATLAB, which requires a license. The output of this implementation has been validated against my MATLAB results. The script and user documentation are provided below. Please note that advanced MTF analysis features, such as noise consideration and frequency-specific analysis, are not included in this general-purpose version due to their application-dependent nature. 

MTF Calculator (Python GUI App) - User Documentation

Chuong Tran

Version: 1.0 (as of March 18, 2025)

Introduction:

The MTF Calculator is a Python graphical user interface (GUI) application designed to estimate the Modulation Transfer Function (MTF) of an imaging system from a captured image containing a slanted edge.

MTF is a crucial metric for characterizing the spatial resolution and sharpness of an optical system. 1 This tool allows users to load an image, select a Region of Interest (ROI) containing a slanted edge, and calculate the MTF based on the analysis of the edge profile. The application also provides visualizations of the Edge Spread Function (ESF) and the resulting MTF curve, along with the ability to export the MTF data to a CSV file and capture a screenshot of the GUI.  

1. What Is the Modulation Transfer Function? | Olympus LS - Evident Scientific

evidentscientific.com

Key Features:

• Image Loading: Supports loading common image file formats (PNG, JPG, JPEG, TIF, BMP). Grayscale images are recommended for optimal analysis.

• Region of Interest (ROI) Selection: Users can interactively select a rectangular ROI within the loaded image that contains a well-defined slanted edge.

• Slanted Edge Analysis: The application analyzes the intensity profile across the selected slanted edge to derive the Edge Spread Function (ESF).

• MTF Calculation: From the ESF, the application calculates the Line Spread Function (LSF) by differentiation and then computes the MTF using the Fast Fourier Transform (FFT).

• Horizontal/Vertical Profile Selection: Users can choose to analyze the slanted edge using predominantly horizontal or vertical intensity profiles within the ROI, depending on the edge orientation.

• ESF Visualization: Displays a plot of the calculated Edge Spread Function, showing the normalized intensity transition across the edge.

• MTF Visualization: Presents the resulting Modulation Transfer Function as a plot of MTF value versus spatial frequency (cycles/pixel).

• MTF50 and MTF10 Markers: The MTF plot includes optional vertical lines indicating the spatial frequencies at which the MTF drops to 50% (MTF50) and 10% (MTF10), providing quick insights into the system's resolution limits.

• MTF Data Export: Allows users to save the calculated MTF data (spatial frequencies and corresponding MTF values) to a comma-separated values (CSV) file for further analysis or reporting.

• Screen Capture: Provides a feature to capture and save the entire GUI panel as a PNG image, useful for documentation or sharing results.

• Intuitive GUI: Features a user-friendly interface with clear controls and visual feedback, making MTF analysis accessible.

Workflow:

1. Load Image: Click the "Load Image" button and select an image file containing a slanted edge. The loaded image will be displayed in the "Loaded Image" panel.

2. Select ROI: Click the "Select ROI" button. The cursor will change to a crosshair. Click and drag on the "Loaded Image" panel to draw a rectangle encompassing a clear, well-defined slanted edge. Release the mouse button to finalize the ROI selection. Ensure the edge is not perfectly horizontal or vertical for optimal analysis.

3. Choose Profile Direction: In the "ROI Profile Direction" section, select either "Horizontal" or "Vertical" depending on the general orientation of the slanted edge within your ROI.

4. Calculate MTF: Click the "Calculate MTF" button. The application will analyze the selected ROI, calculate the ESF and MTF, and display the corresponding plots in the "Edge Spread Function (ESF)" and "MTF Plot" panels. MTF50 and MTF10 markers may appear on the MTF plot if successfully calculated.

5. Export MTF (Optional): If you wish to save the numerical MTF data, click the "Export MTF (CSV)" button. You will be prompted to choose a file name and location to save the CSV file.

6. Capture Screen (Optional): To save a snapshot of the entire MTF Calculator window, click the "Capture Screen" button and choose a file name and location for the PNG image.

7. Repeat: To analyze a different ROI or a different image, repeat the steps above. You can load a new image, select a new ROI, and recalculate the MTF.

Recommendations for Accurate MTF Estimation:

• High-Quality Slanted Edge: The accuracy of the MTF estimation heavily depends on the quality of the slanted edge in the image. The edge should be sharp, have a good contrast between the light and dark regions, and be relatively straight within the ROI.

• Sufficient Edge Angle: The slanted edge should ideally have an angle of a few degrees (e.g., around 5 degrees) with respect to the pixel grid (neither perfectly horizontal nor vertical). This subsampling allows for more accurate reconstruction of the continuous edge profile.

• Appropriate ROI Size: The ROI should be large enough to contain a significant portion of the edge transition and some surrounding area for proper analysis. However, it should not include other sharp features or edges.

• Grayscale Images: While the application might work with color images, converting them to grayscale before analysis is generally recommended to simplify the edge profile.

• Blur Considerations: The MTF calculation includes an optional internal blurring step. While the default settings are usually appropriate, advanced users might consider the potential impact of pre-existing blur in the image.

Limitations:

• The accuracy of the MTF estimation is subject to the quality of the input image and the characteristics of the slanted edge.

• This tool provides an estimate based on a single slanted edge within a specific ROI. The overall MTF of the imaging system might vary across the image plane.

• Advanced MTF analysis techniques, such as accounting for noise or performing frequency-specific analysis, are not included in this version.

Contact:

For questions or feedback regarding the MTF Calculator, please refer to the documentation or contact the developer.

This document provides a comprehensive overview of the MTF Calculator application and its functionality. By following the outlined workflow and considering the recommendations, users can effectively utilize this tool to assess the spatial resolution characteristics of their imaging systems.