Ghost imaging for remote sensing: Experimental demonstration utilizing humidifier-simulated fog

Abstract

Imaging under challenging atmospheric conditions, such as fog or haze, poses a substantial challenge in remote sensing due to light scattering and signal degradation inherent in conventional imaging methods. To address this issue, this paper presents a practical experimental demonstration of ghost imaging (GI) through water fog simulated by a humidifier, highlighting its potential for remote sensing under adverse conditions. Utilizing a controlled fog chamber, LED illumination, a digital micromirror device (DMD), and a single-pixel detector (SPD), we demonstrate that GI can reconstruct images under dense fog ($\beta =2.87\text{dB/m}$) with minimal measurements and achieve high-quality results at a low sampling ratio (3%) under medium fog ($\beta =0.40\text{dB/m}$). Furthermore, post-processing enhancement techniques, including guided filtering, Contrast Limited Adaptive Histogram Equalization (CLAHE), and denoising, are applied to enhance the quality of the reconstructed images by addressing GI-specific challenges, such as correlation-based noise and artifacts. This work provides empirical evidence for the feasibility of GI in foggy environments, paving the way for applications in autonomous navigation and environmental monitoring.