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Single-Pixel Imaging and Identification

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Optics and Lasers".

Deadline for manuscript submissions: 20 June 2025 | Viewed by 395

Special Issue Editor


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Guest Editor
School of Science, China University of Geosciences, Beijing 100083, China
Interests: ghost imaging; single-pixel imaging; identification of moving object

Special Issue Information

Dear Colleagues, 

This Special Issue focuses on the development and application of single-pixel imaging and ghost imaging technology. Single-pixel imaging, a type of computational imaging, originated from ghost imaging technology and achieves imaging through structured light illumination and the collection of light intensity information using a single-pixel detector. Ghost imaging underwent a development process from quantum ghost imaging to classical ghost imaging and then to computational ghost imaging. Combining deep learning algorithms for single-pixel imaging and moving object recognition has significant application advantages, especially in special bands such as infrared and terahertz bands. We welcome manuscripts involving theoretical and experimental research in related fields.

Prof. Lu Gao
Guest Editor

Manuscript Submission Information

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Keywords

  • ghost imaging
  • single-pixel imaging
  • recognition of moving object
  • deep learning
  • computational imaging

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Published Papers (1 paper)

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Research

24 pages, 2032 KiB  
Article
ViT-Based Classification and Self-Supervised 3D Human Mesh Generation from NIR Single-Pixel Imaging
by Carlos Osorio Quero, Daniel Durini and Jose Martinez-Carranza
Appl. Sci. 2025, 15(11), 6138; https://doi.org/10.3390/app15116138 - 29 May 2025
Viewed by 205
Abstract
Accurately estimating 3D human pose and body shape from a single monocular image remains challenging, especially under poor lighting or occlusions. Traditional RGB-based methods struggle in such conditions, whereas single-pixel imaging (SPI) in the Near-Infrared (NIR) spectrum offers a robust alternative. NIR penetrates [...] Read more.
Accurately estimating 3D human pose and body shape from a single monocular image remains challenging, especially under poor lighting or occlusions. Traditional RGB-based methods struggle in such conditions, whereas single-pixel imaging (SPI) in the Near-Infrared (NIR) spectrum offers a robust alternative. NIR penetrates clothing and adapts to illumination changes, enhancing body shape and pose estimation. This work explores an SPI camera (850–1550 nm) with Time-of-Flight (TOF) technology for human detection in low-light conditions. SPI-derived point clouds are processed using a Vision Transformer (ViT) to align poses with a predefined SMPL-X model. A self-supervised PointNet++ network estimates global rotation, translation, body shape, and pose, enabling precise 3D human mesh reconstruction. Laboratory experiments simulating night-time conditions validate NIR-SPI’s potential for real-world applications, including human detection in rescue missions. Full article
(This article belongs to the Special Issue Single-Pixel Imaging and Identification)
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