# Resolving Gas Bubbles Ascending in Liquid Metal from Low-SNR Neutron Radiography Images
## 5 Experimental Validation
### Moving Reference Body  
The principles behind imaging a moving reference body are as above, except the body is now attached to a pendulum (Figure 22) that periodically swings, and thus the body travels back and forth through the FOV. The pendulum is a standard laboratory holder that  
Figure 21: Neighborhood analysis for the reference spherical void, transmission along the longer axis with a extra distance to the scintillator: normalized width mean of luminance (gray) over the length of (**a**) horizontal and (**b**) vertical patches roughly fit to the sphere dimensions, spanning the cropped body images. is suspended from above the neutron beam with the reference body fixed by its clamps. The motion is mostly horizontal and is initially strongly damped until the pendulum amplitude reaches a state where its oscillations exhibit a very slow decay. This enables us to determine the dynamics of the error metrics outlined in Section 5.1 and assess the effects of motion blur as the body and the void within it decelerate. Here, before the global and local filters can be applied to the cropped reference body images, one must first segment the body within the FOV (Figure 22), crop the masked image to an IW about the mask centroid, repair the IW images as necessary, and then apply the filters. This procedure is somewhat more involved that the one in Section 5.1 and is outlined in Algorithm 8. ```
Input: A normalized pre-processed (Algorithm 2) image as in Figure 22 Image filtering
1 Poisson TV filtering (4)
2 Luminance map inversion SCTMM filtering (7)
3 Image normalization
4 Reference body segmentation Chan-Vese binarization (11)
5 Morphological opening (disk elements)
6 Morphological erosion (disk elements)
7 Delete border components
8 Void region extraction Mask area thresholding
9 Define an IW about the body centroid based on the body segment area (8) and (9)
10 Project the input image onto the IW masking the pixels outside the body segment Void region restoration
11 Body background extrapolation to masked IW regions using texture synthesis-based inpainting
12 Image normalization
13 (Optional) Remove high-luminance outliers and normalize the image
14 Output: A repaired IW containing the spherical void surrounded by the body background
```  
**Algorithm 8**Void region (IW) extraction and repair from the pendulum images. Figure 22: Neutron radiography image of the pendulum used for the reference experiments with the moving reference body: neutron flux transmission along the (**a**) longer and (**b**) shorter axes. The red dotted arrows indicate the direction of motion and the white dotted circles highlight the locations of the spherical void. The pendulum arm is a standard lab holder and the reference body is held by clamps (dashed orange lines). Note the motion blur visible at the body boundaries and the holder arms above the clamps. The Poisson TV filter (4) reduces the noise in the image and the image luminance map inversion makes the darker body area foreground and the surrounding air (brighter) background. The SCTMM filter (7) then increases the body CNR and the body is segmented using the Chan-Vese process (11). Morphological opening (disk structural elements, 15-pixel radius) and erosion (disk structural elements, 5-pixel radius) help separate the body from the clamps (Figure 22), as well as to remove artefacts, if any. Border component removal is done because only body segments fully within the FOV are eligible for analysis. Note that here we use \(c=0.5\) for SCTMM and \(\beta=1\) for the TV filter. After area thresholding removes mask components that have abnormally small areas (usually left over clamp segment fragments), an IW is defined about the body centroid via (8) and (9) with \(s=1.25\), and the input image with masked non-segment pixels is projected onto the IW. An example is illustrated in Figure 23. Note that (a), which shows the detected segments, contains a small artefact to the bottom left of the body segment--such segments are removed by area thresholding.