Partial Coherence for Object Recognition and Depth Sensing

Zichen Xie, Ken Xingze Wang
11/14/2023
cs.CVphysics.optics

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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.

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Cite this paper

@article{xie2023partial,
  title  = {Partial Coherence for Object Recognition and Depth Sensing},
  author = {Zichen Xie and Ken Xingze Wang},
  year   = {2023},
  eprint = {2401.02432},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2401.02432v1}
}

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