Rutgers University 3 credits Electrical and Computer Engineering
In computational imaging, optical encoding methods, as done in digital holography or magnetic resonance imaging (MRI), allow us to capture images from the depths of the human body to the far reaches of space. In such systems, the acquired signals are not the desired images, but functions of them, as determined by the optical encoding. Solving the corresponding inverse problems allows us to recover the desired images. Throughout this course, we’ll examine a variety of inverse problems, looking at both classic and modern computational imaging techniques. We’ll dissect the imaging systems tied to these problems and delve into algorithm development for solving them. With machine learning leading the charge in today’s imaging solutions, we will also explore how these techniques are integrated into solving inverse problems. Prerequisites/Corequisites: Senior and graduate student only. Linear Algebra experience necessary.
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