Partial Coherence for Object Recognition and Depth Sensing
Computer Vision and Pattern Recognition
2024-01-08 v1 Optics
Abstract
We show a monotonic relationship between performances of various computer vision tasks versus degrees of coherence of illumination. We simulate partially coherent illumination using computational methods, propagate the lightwave to form images, and subsequently employ a deep neural network to perform object recognition and depth sensing tasks. In each controlled experiment, we discover that, increased coherent length leads to improved image entropy, as well as enhanced object recognition and depth sensing performance.
Keywords
Cite
@article{arxiv.2401.02432,
title = {Partial Coherence for Object Recognition and Depth Sensing},
author = {Zichen Xie and Ken Xingze Wang},
journal= {arXiv preprint arXiv:2401.02432},
year = {2024}
}