Detection of Laser Optic Defects Using Gradient Direction Matching

That National Ignition Facility (NIF) at Lawrence Livermore National Laboratory (LLNL) will be the world's largest and most energetic laser. It has thousands of optics and depends heavily on the quality and performance of these optics. Over the past several years, we have developed the NIF Optics Inspection Analysis System that automatically finds defects in a specific optic by analyzing images taken of that optic. This paper describes a new and complementary approach for the automatic detection of defects based on detecting the diffraction ring patterns in downstream optic images caused by defects in upstream optics. Our approach applies a robust pattern matching algorithm for images called Gradient Direction Matching (GDM). GDM compares the gradient directions (the direction of flow from dark to light) of pixels in a test image to those of a specified model and identifies regions in the test image whose gradient directions are most in line with those of the specified model. For finding rings, we use luminance disk models whose pixels have gradient directions all pointing toward the center of the disk. After GDM identifies potential rings locations, we rank these rings by how well they fit the theoretical diffraction ring pattern equation. We perform false alarm mitigation by throwing out rings of low fit. A byproduct of this fitting procedure is an estimate of the size of the defect and its distance from the image plane. We demonstrate the potential effectiveness of this approach by showing examples of rings detected in real images of NIF optics