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Related Experiment Video

Updated: Feb 20, 2026

Scattering And Absorption of Light in Planetary Regoliths

Scattering And Absorption of Light in Planetary Regoliths

Published on: July 1, 2019

Learning-based focusing through scattering media.

Ryoichi Horisaki, Ryosuke Takagi, Jun Tanida

|October 20, 2017

Summary

This summary is machine-generated.

We developed a machine-learning method to focus light through scattering media. This model-free approach computationally inverts optical processes, enabling precise light control even when the medium

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Last Updated: Feb 20, 2026

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Area of Science:

Optics and Photonics
Machine Learning
Computational Imaging

Background:

Scattering media distort and randomize light propagation, posing challenges for optical focusing.
Traditional methods require precise knowledge of the scattering medium's optical properties.

Purpose of the Study:

To develop a model-free machine learning method for achieving light focusing through complex scattering media.
To demonstrate the efficacy of computational inversion of optical processes for controlling light fields.

Main Methods:

Utilizing a nonlinear regression algorithm trained on input-output pairs to computationally invert the scattering process.
Employing a spatial light modulator for double modulation to introduce necessary nonlinearity.
Experimental validation of the light focusing technique.

Main Results:

Successfully demonstrated light focusing through a scattering medium using the machine learning approach.
Achieved precise control over optical fields without prior knowledge of the medium's model.
The method effectively manages randomness inherent in scattering phenomena.

Conclusions:

The presented machine-learning-based method offers a robust solution for light focusing in scattering environments.
This model-free approach significantly advances the control of light in complex optical systems.
Opens new possibilities for applications in imaging, microscopy, and optical manipulation through scattering media.