Dictionary based image enhancement for integrated circuit imaging

The rapid decrease in the dimensions of integrated circuits has necessitated corresponding higher-resolution methods for defect imaging. Current state of the art, defect imaging systems are reaching the limits of their resolution. In this work, we are proposing a new overcomplete dictionary based sparse signal imaging framework to improve the resolution and localization in confocal microscopy systems for backside optical integrated circuit defect imaging. The domain of integrated circuit imaging is particularly suitable for the application of overcomplete dictionaries in an image reconstruction framework because the images are highly structured, containing predictable building blocks derivable from the corresponding computer aided design layouts. This structure provides a strong and natural a-priori dictionary for scene reconstruction. This dictionary prior is coupled with a physically-based observation model to create enhanced scene reconstructions. The approach is described and results on simulated data are provided.