(Peer-Reviewed) Data-driven polarimetric approaches fuel computational imaging expansion
Sylvain Gigan
Laboratoire Kastler Brossel, École Normale Supérieure/PSL Research University, Paris 75005, France
Opto-Electronic Advances, 2024-09-25
Abstract
Incorporating polarization in computer vision tasks provides new solutions to high-level analytics, in particular when coupled with machine learning frameworks such as convolutional neural networks (CNN). A recent review in Opto-Electronic Science reports on the developments in data-driven polarimetric imaging, including polarimetric descattering, 3D imaging, reflection removal, target detection and biomedical imaging. The review carefully analyzes these new trends with their advantages and disadvantages, and provides a general insight for future research and development.
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