Photon-starved imaging through turbulence at the diffraction limit

TL;DR

This paper introduces TAP-BD, a novel physics-informed blind deconvolution framework that enables reliable, diffraction-limited imaging through atmospheric turbulence under photon-starved conditions, outperforming existing methods.

Contribution

The paper presents TAP-BD, a new approach that combines phase diversity and physics-based optimization to recover images and turbulence effects with minimal measurements in photon-starved regimes.

Findings

TAP-BD reliably reconstructs scenes with few measurements.

It performs well under strong turbulence and low photon conditions.

Outperforms conventional adaptive optics and speckle imaging methods.

Abstract

Ground-based imaging systems struggle to achieve diffraction-limited resolution when atmospheric turbulence and photon scarcity act simultaneously. In this regime, conventional adaptive optics, speckle imaging, and blind deconvolution lack sufficient information diversity to reliably estimate either the scene or the turbulence. We present Turbulence Aware Poisson Blind Deconvolution (TAP-BD), a framework designed for robust image recovery in these extreme conditions. TAP-BD extracts more information from coded-detection through phase diversity and decodes it with a physics-informed optimization that incorporates low photon Poisson statistics. Experiments show that TAP-BD provides reliable reconstructions of both scene and turbulence using only a few tens of measurements, even under strong aberrations and photon-starved conditions where existing methods fail. This capability enables photon-efficient, turbulence resilient imaging for applications such as space situational awareness and long-range remote sensing.