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Ghost Imaging for Remote Sensing

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing Image Processing".

Deadline for manuscript submissions: closed (15 April 2019) | Viewed by 10788

Special Issue Editor


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Guest Editor
Electrical and Computer Engineering, Lehigh University, Bethlehem, PA 18015, USA
Interests: imaging techniques; nano-measurement; remote sensing; image processing; image restoration; nonlinear optics; lasers; optical parametric oscillation; terahertz’s generation and applications
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Ghost imaging holds promise for important applications, such as remote sensing in a low-level light environment. In a ghost imaging setup, a camera, which functions as a single-pixel bucket-like detector, aims and monitors the surface of a target, while a reference camera with a high spatial resolution measures fluctuations of light affected by the surroundings from a wider field of view. Such fluctuations can be pre-determined. Coincidence detection of the target and surroundings reveals the structure of the target, as well as information about the surrounding environment. After all the data collected by employing such an imaging setup are processed by complex algorithms, the processed data provide a rich spectrum of information about the target. What is unique about ghost imaging lies in its capability of providing better sensitivity than all the other conventional imaging techniques, in a low-level light environment. Moreover, such a technique has applications in 3D remote sensing, object tracking, imaging through turbid media, super-resolution imaging, and so on.

Recently, there has been an increasing interest in reaching high resolutions in imaging under low-level light conditions and/or through turbid media. Ghost imaging sheds light on how to achieve such a goal. There are many parameters affecting the performance of ghost imaging protocols in the resolution and visibility of images, such as light sources, designs of optical path, propagation distance, image processing, and so on. Deep learning and other AI tools have been introduced in the literature for improving the performance of ghost imaging.

We call for original papers on topics relevant to ghost imaging. These seminal contributions are expected to bring about novel ideas in order to build more sensitive and innovative setups for the applications of ghost imaging in remote sensing.

 The topics of interest for this Special Issue on “Ghost imaging for remote sensing” include, but are not limited to:

  • Novel theories and concepts in ghost imaging
  • Quantum ghost imaging based on non-classical phenomena
  • Reflection and transmission configurations for ghost imaging systems and protocols
  • Advances in optical tools for ghost imaging in remote sensing
  • Development of laser sources and beam path designs in ghost imaging
  • Frontier in computational ghost imaging
  • Image processing algorithms optimized to data collection in ghost imaging
  • Emerging deep learning and other artificial intelligence techniques for ghost imaging
  • Comparison study of ghost imaging with other imaging techniques
  • Applications of ghost imaging in remote sensing, especially in the presence of turbulent and other distorting media.
Dr. Pengda Hong
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Ghost imaging
  • Reflection and transmission configurations
  • Optical protocols
  • Computational imaging
  • Imaging processing
  • Deep learning
  • Remote sensing

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Published Papers (2 papers)

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15 pages, 6953 KiB  
Article
Phaseless Radar Coincidence Imaging with a MIMO SAR Platform
by Aaron V. Diebold, Mohammadreza F. Imani and David R. Smith
Remote Sens. 2019, 11(5), 533; https://doi.org/10.3390/rs11050533 - 5 Mar 2019
Cited by 12 | Viewed by 4822
Abstract
The correlation-based synthetic aperture radar imaging technique, termed radar coincidence imaging, is extended to a fully multistatic multiple-input multiple-output (MIMO) synthetic aperture radar (SAR) configuration. Within this framework, we explore two distinct processing schemes: incoherent processing of intensity data, obtained using asynchronous receivers [...] Read more.
The correlation-based synthetic aperture radar imaging technique, termed radar coincidence imaging, is extended to a fully multistatic multiple-input multiple-output (MIMO) synthetic aperture radar (SAR) configuration. Within this framework, we explore two distinct processing schemes: incoherent processing of intensity data, obtained using asynchronous receivers and inspired by optical ghost imaging works, and coherent processing with synchronized array elements. Improvement in resolution and image quality is demonstrated in both cases using numerical simulations that model an airborne MIMO SAR system at microwave frequencies. Finally, we explore methods for reducing measurement times and computational loads through compressive and gradient image reconstruction using phaseless data. Full article
(This article belongs to the Special Issue Ghost Imaging for Remote Sensing)
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Other

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8 pages, 3887 KiB  
Letter
Airborne Near Infrared Three-Dimensional Ghost Imaging LiDAR via Sparsity Constraint
by Chenglong Wang, Xiaodong Mei, Long Pan, Pengwei Wang, Wang Li, Xin Gao, Zunwang Bo, Mingliang Chen, Wenlin Gong and Shensheng Han
Remote Sens. 2018, 10(5), 732; https://doi.org/10.3390/rs10050732 - 9 May 2018
Cited by 66 | Viewed by 5030
Abstract
Three-dimensional ghost imaging LiDAR via sparsity constraint (3D GISC LiDAR), as a staring imaging method, can obtain both the range information and spatial distribution of a remote target with a single-pixel time-resolved detector. However, previous demonstrations mainly focused on the relatively static scene [...] Read more.
Three-dimensional ghost imaging LiDAR via sparsity constraint (3D GISC LiDAR), as a staring imaging method, can obtain both the range information and spatial distribution of a remote target with a single-pixel time-resolved detector. However, previous demonstrations mainly focused on the relatively static scene in visible light. Here we propose an airborne near infrared 3D GISC LiDAR system and airborne high-resolution imaging is implemented. Experimental results show that an image with 0.48 m horizontal resolution as well as 0.5 m range resolution at approximately 1.04 km height can be achieved. Some considerations on the improvement of this LiDAR system are also discussed. Full article
(This article belongs to the Special Issue Ghost Imaging for Remote Sensing)
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