A single image almost never contains all the information you need. Different lighting conditions reveal different things, and the strongest systems combine several captures.
A typical multi-image set
- Normal exposure for the baseline.
- An overexposed image to separate near-identical materials.
- Different lighting angles to bring out topography.
- A UV image for contamination and coatings.
- An IR image for material penetration.
Each reveals different information. Fusing them gives the algorithm far more to work with than any single frame ever could.
The trade-off
More images means more acquisition time and more processing. The art is choosing the smallest set of images that fully separates the defect from everything else.