Estimate Blur ModelΒΆ

  • To estimate the blur model, we must acquire radiographs of a sharp edge such as a Tungsten rollbar. Each sharp edge radiograph can either contain a single straight edge or two mutually perpendicular intersecting edges. If imaging a single straight edge, then radiographs must be acquired at two different perpendicular orientations of the straight edge. Also, radiographs must be acquired at two different values of SOD/ODD, where SOD is the source to object distance and ODD is the object to detector distance.

  • Next, the radiographs must be appropriately normalized. For each radiograph, acquire a bright field image (measurements with X-rays but no sample) and a dark field image (measurements without X-rays). Then, compute the normalized radiograph by dividing the difference between the radiograph and the dark field image with the difference between the bright field and the dark field image.

  • Using the normalized radiographs, estimate parameters of X-ray source blur and detector blur using the function pysaber.estimate_blur().

  • An example python script that demonstrates blur estimation using radiographs of a single straight edge at various orientations and SOD/ODD values is shown below. To obtain the data that is required to run this script, download and unzip the zip file at the link data. To run the script as is within the current working directory, the files in the zip file must be placed within a folder called data.

import numpy as np #For mathematics on vectors
from PIL import Image #To read images in TIFF format
from pysaber import estimate_blur #To estimate blur PSF parameters

pix_wid = 0.675 #Width of each pixel in micrometers

#Horizontal and vertical edge radiographs
edge_files = ['data/horz_edge_25mm.tif','data/horz_edge_50mm.tif',
#Filenames of bright field images for normalization
bright_files = ['data/horz_bright.tif','data/horz_bright.tif',
#Filenames of dark field images for normalization
dark_files = ['data/horz_dark.tif','data/horz_dark.tif',
#Source to object (SOD) distances in micrometers for each radiograph in edge_files
sod = [24751.89,50251.79,24753.05,50253.35] 
#Source to detector (SDD) distances in micrometers for each radiograph in edge_files
sdd = [71003.08,71003.08,71010.86,71010.86] 

rads = [] #List that will contain normalized radiographs
odd = [] #Object to detector distance (ODD) for each radiograph in rads
for i in range(len(edge_files)): #Loop through all the radiograph files
    rad =[i]) #Read radiograph
    rad = np.asarray(rad) #Convert to numpy array
    bright =[i]) #Read bright field
    bright = np.asarray(bright) #Convert to numpy array
    dark =[i]) #Read dark field
    dark = np.asarray(dark) #Convert to numpy array
    nrad = (rad-dark)/(bright-dark) #Normalize radiograph
    rads.append(nrad) #Add normalized radiograph to the list rads
    odd.append(sdd[i]-sod[i]) #Add corresponding ODD to the list odd

#Estimate X-ray source blur, detector blur, and every radiograph's transmission function
#To reduce run time and quickly produce a result, the value for argument thresh can be reduced.
#However, reducing thresh may produce an inaccurate blur model that does not fit the measured data  
src_params,det_params,trans_params = estimate_blur(rads,sod,odd,pix_wid,
#src_params is a python dictionary of parameters that quantify X-ray source blur
#det_params is a python dictionary of parameters that quantify blur from the detector panel
#Both src_params and det_params characterize the effective blur and are used during deblurring 
#trans_params is a list of lists, each of which contains the low/high values of transmission function
#trans_params is useful to check accuracy of fit and not useful for deblurring. 

#Uncomment above line to get help on using the function estimate_blur

print("Source blur model parameters are {}".format(src_params)) 
#Print parameters of source blur
print("Detector blur model parameters are {}".format(det_params)) 
#Print parameters of detector blur
print("Transmission function parameters are {}".format(trans_params)) 
#Print parameters of transmission functions