4 citations · 5 across the 11 of their papers we have counts for
11 papers
Spatio-Temporal Turbulence Mitigation: A Translational Perspective
Xingguang Zhang, Nicholas Chimitt, Yiheng Chi +2
Recovering images distorted by atmospheric turbulence is a challenging inverse problem due to the stochastic nature of turbulence. Although numerous turbulence mitigation (TM) algo…
FarSight: A Physics-Driven Whole-Body Biometric System at Large Distance and Altitude
Feng Liu, Ryan Ashbaugh, Nicholas Chimitt +17
Whole-body biometric recognition is an important area of research due to its vast applications in law enforcement, border security, and surveillance. This paper presents the end-to…
Structured Kernel Estimation for Photon-Limited Deconvolution
Yash Sanghvi, Zhiyuan Mao, Stanley H. Chan
Images taken in a low light condition with the presence of camera shake suffer from motion blur and photon shot noise. While state-of-the-art image restoration networks show promis…
Real-Time Dense Field Phase-to-Space Simulation of Imaging through Atmospheric Turbulence
Nicholas Chimitt, Xingguang Zhang, Zhiyuan Mao +1
Numerical simulation of atmospheric turbulence is one of the biggest bottlenecks in developing computational techniques for solving the inverse problem in long-range imaging. The c…
Photon-Limited Blind Deconvolution using Unsupervised Iterative Kernel Estimation
Yash Sanghvi, Abhiram Gnanasambandam, Zhiyuan Mao +1
Blind deconvolution is a challenging problem, but in low-light it is even more difficult. Existing algorithms, both classical and deep-learning based, are not designed for this con…
Single Frame Atmospheric Turbulence Mitigation: A Benchmark Study and A New Physics-Inspired Transformer Model
Zhiyuan Mao, Ajay Jaiswal, Zhangyang Wang +1
Image restoration algorithms for atmospheric turbulence are known to be much more challenging to design than traditional ones such as blur or noise because the distortion caused by…
Imaging through the Atmosphere using Turbulence Mitigation Transformer
Xingguang Zhang, Zhiyuan Mao, Nicholas Chimitt +1
Restoring images distorted by atmospheric turbulence is a ubiquitous problem in long-range imaging applications. While existing deep-learning-based methods have demonstrated promis…
Accelerating Atmospheric Turbulence Simulation via Learned Phase-to-Space Transform
Zhiyuan Mao, Nicholas Chimitt, Stanley H. Chan
Fast and accurate simulation of imaging through atmospheric turbulence is essential for developing turbulence mitigation algorithms. Recognizing the limitations of previous approac…
Student-Teacher Learning from Clean Inputs to Noisy Inputs
Guanzhe Hong, Zhiyuan Mao, Xiaojun Lin +1
Feature-based student-teacher learning, a training method that encourages the student's hidden features to mimic those of the teacher network, is empirically successful in transfer…
Image Reconstruction of Static and Dynamic Scenes through Anisoplanatic Turbulence
Zhiyuan Mao, Nicholas Chimitt, Stanley Chan
Ground based long-range passive imaging systems often suffer from degraded image quality due to a turbulent atmosphere. While methods exist for removing such turbulent distortions,…
Rethinking Atmospheric Turbulence Mitigation
Nicholas Chimitt, Zhiyuan Mao, Guanzhe Hong +1
State-of-the-art atmospheric turbulence image restoration methods utilize standard image processing tools such as optical flow, lucky region and blind deconvolution to restore the…