Computational Imaging for Optical Super-resolution and Source Separation
|Event Date:||June 28, 2017|
|Speaker:||Dr. Aswin Sankaranarayanan|
|Speaker Affiliation:||Assistant Professor, Electrical & Computer Engineering –
Carnegie Mellon University
|Type:||Integrated Imaging Seminar
|Contact Name:||Professor Charles Bouman
|School or Program:||Electrical and Computer Engineering
The basic design of the camera — a lens and an imaging sensor — has remain unchanged for many centuries. While this design has been perfected for photography, there are many current and upcoming application domains where it is woefully inadequate. I will discuss a few examples from my research including high-resolution imaging in infrared, extremely with thin form-factor cameras, and enabling post-process freedom in manipulating photographs. In each example, I will discuss research from my work on novel imaging designs and associated image processing techniques that provide capabilities that far exceed those of the conventional design. Central to the talk is the idea of computational imaging, the co-design of optics and processing to supplant the limitations of conventional imaging designs.
Aswin Sankaranarayanan is an Assistant Professor at Carnegie Mellon University (CMU). He earned his Ph.D. from University of Maryland, College Park. He was a post-doctoral researcher at the DSP group at Rice University before joining the faculty at the ECE Department at CMU in 2013. Aswin is the PI of the Image Science Lab at CMU; his research spans topics in imaging, machine vision, and image processing. He is the recipient of the NSF CAREER award in 2017, the 2016 Herschel M. Rich invention award from Rice University for work on lensless imaging, and the distinguished dissertation fellowship from the ECE Department at University of Maryland for his thesis work in 2009.