Learn how to measure the full width at half maximum (FWHM) of a peak in an image using Python.
The full width at half maximum (FWHM) is a measure of the width of a peak in an image. It is calculated as the distance between the points on the peak where the intensity is half of its maximum value.
In this article, we will discuss how to measure the FWHM of a peak in an image using Python. We will use the scipy.ndimage.gaussian_filter() function to smooth the image and the scipy.signal.find_peaks() function to find the peaks in the image.
Step 1: Import The Necessary Libraries
The first step is to import the necessary libraries. We will need the following libraries:
- NumPy: This library provides a high-level interface to multi-dimensional arrays.
- SciPy: This library provides a collection of scientific computing tools.
- Matplotlib: This library provides a plotting library.
Step 2: Load The Image
The next step is to load the image. We can do this using the imread() function from the OpenCV library.
Step 3: Smooth the image
The next step is to smooth the image. This will help to reduce noise in the image and make it easier to find the peaks. We can do this using the gaussian_filter() function from the scipy.ndimage library.
import scipy.ndimage
smoothed_image = scipy.ndimage.gaussian_filter(image, sigma=3)Step 4: Find the peaks in the image
The next step is to find the peaks in the image. We can do this using the find_peaks() function from the scipy.signal library.
import scipy.signal
peaks = scipy.signal.find_peaks(smoothed_image)Step 5: Calculate the FWHM of each peak
The final step is to calculate the FWHM of each peak. We can do this by finding the distance between the points on the peak where the intensity is half of its maximum value.
for peak in peaks:
left_index = peak[0] - int(FWHM / 2)
right_index = peak[0] + int(FWHM / 2)
fwhm = smoothed_image[left_index:right_index].std()Conclusion
In this article, we have discussed how to measure the FWHM of a peak in an image using Python. We have used the scipy.ndimage.gaussian_filter() function to smooth the image and the scipy.signal.find_peaks() function to find the peaks in the image. We have then calculated the FWHM of each peak by finding the distance between the points on the peak where the intensity is half of its maximum value.
This is just a basic introduction to measuring FWHM from an image in Python. There are many other ways to do this, and the best approach will depend on the specific image and the desired accuracy.
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