Imaging through scattering is an important yet challenging problem. Tremendous progress
has been made by exploiting the deterministic input–output “transmission matrix” for a fixed …

Coherent imaging through scatter is a challenging task. Both model-based and data-driven
approaches have been explored to solve the inverse scattering problem. In our previous …

Imaging through scattering media is one of the hotspots in the optical field, and impressive
results have been demonstrated via deep learning (DL). However, most of the DL …

Computational imaging through scatter generally is accomplished by first characterizing the
scattering medium so that its forward operator is obtained and then imposing additional …

Optical imaging in scattering media is important to many fields but remains challenging.
Recent methods have focused on imaging through thin scattering layers or thicker scattering …

We demonstrate an imaging technique that allows identification and classification of objects
hidden behind scattering media and is invariant to changes in calibration parameters within …

Deep learning has been broadly applied to imaging in scattering applications. A common
framework is to train a descattering network for image recovery by removing scattering …

The problem of imaging through thick scattering media is encountered in many disciplines of
science, ranging from mesoscopic physics to astronomy. Photons become diffusive after …

Deep learning has broad applications in imaging through scattering media. Polarization, as
a distinctive characteristic of light, exhibits superior stability compared to light intensity within …

We present a machine-learning-based method for single-shot imaging through scattering
media. The inverse scattering process was calculated based on a nonlinear regression …