# Optimal compressive multiphoton imaging at depth using single-pixel detection

## TL;DR

This paper introduces an optimal measurement basis for compressive multiphoton imaging that enhances imaging depth and speed in turbid media using single-pixel detection, leveraging the Morlet basis to minimize diffraction effects.

## Contribution

It demonstrates the use of the random Morlet basis as an optimal set for compressive multiphoton imaging, improving imaging through scattering media with the TRAFIX method.

## Key findings

- Morlet basis reduces diffraction and scattering effects.
- TRAFIX enables deep tissue imaging without correction.
- Enhanced imaging speed and reduced photodamage.

## Abstract

Compressive sensing can overcome the Nyquist criterion and record images with a fraction of the usual number of measurements required. However, conventional measurement bases are susceptible to diffraction and scattering, prevalent in high-resolution microscopy. Here, we explore the random Morlet basis as an optimal set for compressive multiphoton imaging, based on its ability to minimise the space-frequency uncertainty. We implement this approach for the newly developed method of wide-field multiphoton microscopy with single-pixel detection (TRAFIX), which allows imaging through turbid media without correction. The Morlet basis is well-suited to TRAFIX at depth, and promises a route for rapid acquisition with low photodamage.