Foundations of Computational Imaging

4.0 credits · Undergraduate

This course will provide students with a mathematical and algorithmic framework for computational imaging. Computational imaging blends hardware and software design to overcome the limits of traditional imaging systems. Computational imaging is the foundation for many scientific and medical imaging systems, including magnetic resonance imaging (MRI), computed tomography (CT), light-field imaging, and phase microscopy, and has enabled exciting breakthroughs, such as capturing the first image of a black hole. Students will learn how to formulate and solve imaging inverse problems, in which signals (typically images or volumes) are recovered from indirect or incomplete data using a variety of tools from optimization, signal processing, machine learning, and generative methods.