Deep speckle correlation: a deep learning approach toward scalable imaging through scattering media
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 …
has been made by exploiting the deterministic input–output “transmission matrix” for a fixed …
Displacement-agnostic coherent imaging through scatter with an interpretable deep neural network
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 …
approaches have been explored to solve the inverse scattering problem. In our previous …
Imaging through unknown scattering media based on physics-informed learning
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 …
results have been demonstrated via deep learning (DL). However, most of the DL …
Imaging through glass diffusers using densely connected convolutional networks
Computational imaging through scatter generally is accomplished by first characterizing the
scattering medium so that its forward operator is obtained and then imposing additional …
scattering medium so that its forward operator is obtained and then imposing additional …
Overlapping speckle correlation algorithm for high-resolution imaging and tracking of objects in unknown scattering media
Y Shi, W Sheng, Y Fu, Y Liu - Nature Communications, 2023 - nature.com
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 …
Recent methods have focused on imaging through thin scattering layers or thicker scattering …
Object classification through scattering media with deep learning on time resolved measurement
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 …
hidden behind scattering media and is invariant to changes in calibration parameters within …
Adaptive 3D descattering with a dynamic synthesis network
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 …
framework is to train a descattering network for image recovery by removing scattering …
[HTML][HTML] Learning-based lensless imaging through optically thick scattering media
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 …
science, ranging from mesoscopic physics to astronomy. Photons become diffusive after …
Dynamic polarization fusion network (DPFN) for imaging in different scattering systems
B Lin, X Fan, P Peng, Z Guo - Optics Express, 2023 - opg.optica.org
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 …
a distinctive characteristic of light, exhibits superior stability compared to light intensity within …
Learning-based imaging through scattering media
R Horisaki, R Takagi, J Tanida - Optics express, 2016 - opg.optica.org
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 …
media. The inverse scattering process was calculated based on a nonlinear regression …