Defocus and Aberration Modeling for RGB-Infrared Cameras

Conventional camera sensors record three color channels: red, green and blue. In this project we will investigate computational photography algorithms for cameras that record a near-infrared channel (NIR) in addition to RGB. This channel is particularly useful for biometric imaging and holds great potential in consumer imaging applications as well. The key challenge in simultaneously capturing RGB and NIR is that lens behavior depends on wavelenth and thus the NIR channel may be defocused compared to the other three. Our aim will be to study this lens behavior in detail and propose demosaicing/deblurring algorithms for high-quality RGB-NIR photography. To validate our image formation models and algorithms we will use an RGB-NIR prototype camera developed by Qualcomm as our experimental testbed.

Faculty Supervisor:

Dr. Kiriakos N. Kutulakos

Student:

Huixuan Tang

Partner:

Qualcomm Canada Inc.

Discipline:

Computer science

Sector:

Information and communications technologies

University:

University of Toronto