Computational Optics Group - Adaptive Motion Deblurring
University of Wisconsin-Madison, USA
2022.8 - present
Andreas Velten, PH. D, Assistant Professor at the Department of Biostatistics and medical Informatics, Electrical and Computer Engineering
Trevor Seets, NSF Graduate Research Fellow at Computational Optics Lab
Compressing the camera image can always a problem in real world. Due to SPAD’s unique ability to precisely time-tag individual photons, it has great potential for high-resolution long-range LiDAR systems. We pick the series images captured by SPAD and select change points(by solving optimal problem). Then uses the change points to simulate the original object’s real movement to deblur. Also, we find another way to simulate real images only based on the changes point images, which can speed up the calculation.
Mainly focused on adjusting the deblurring methods used and visualizing results; detecting change points and the deblurred image based on change point videos; also using novel interpolation to optimize the deblurring method.
LINK:https://github.com/wrencanfly/Adaptive_Motion_Deblurring (permission may be required)