Talk Abstract:  Imaging systems are found in many devices; these devices serve many different functions from consumer photography to automotive applications to biometric recognition. Designing these image systems can be quite complex, and the process can benefit from simulation tools that model all of the system components. Simulation can be a tool for optimizing the design or evaluating performance even before building a physical prototype. Furthermore, an accurate simulator can be used to generate a large number of synthetic images which can be used to train or test neural networks.

A significant challenge in simulating an image system is obtaining accurate models of all the components. Understandably, manufacturers may want to protect their intellectual property, making them reluctant to share details that would be important to an accurate simulation. In this talk, I will discuss how we used black-box (phenomenological) models to simulate a consumer camera with a proprietary lens design and proprietary pixel optics (microlens and dual pixel). I will describe the ideas and evaluate the performance of the simulation. The use of phenomenological models can greatly expand the scope and value of image systems simulations.

Speaker Biography:  Thomas Goossens is a postdoctoral fellow at Stanford University working on camera simulation. He obtained his Ph.D. degree at KU Leuven (Belgium) in collaboration with IMEC, working on hyperspectral imaging.

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