Applications of Image Processing and Sensor Systems

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: 15 August 2026 | Viewed by 1673

Special Issue Editors


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Guest Editor
1. Department of Geology and Geological Engineering, Colorado School of Mines, Brown Hall 254b, Golden, CO 80401, USA
2. Department of Data and Business Analytics, Stonehill College, Easton, MA, USA
Interests: remote sensing; InSAR (interferometric synthetic aperture radar); geographic information systems (GIS); spatiotemporal data analysis; machine learning for geospatial applications; environmental monitoring; subsidence and deformation analysis; sensor-based data integration; image processing in earth sciences; data-driven decision support systems

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Co-Guest Editor
Department of Geology and Geological Engineering, Colorado School of Mines, Golden, CO 80401, USA
Interests: remote sensing and GIS applications in geohazard assessment and environmental impact study; SAR and PSInSAR applications in monitoring ground subsidence and landslide deformation rate; underground transportation geotechnics; rock mass characterization; numerical modeling, such as finite element and finite difference methods for ground thermal regimes; stress–strain distribution in the rock or soil mass
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Special Issue Information

Dear Colleagues,

The rapid advancement of sensor technologies and image processing algorithms has unlocked unprecedented opportunities across multiple domains—from environmental monitoring and remote sensing to intelligent transportation and healthcare systems. This Special Issue invites high-quality contributions exploring novel applications, methodologies, and integrations of image processing techniques and sensor systems.

We especially welcome papers focusing on the synergistic use of satellite- and ground-based sensor data, machine learning, and GIS technologies to tackle real-world challenges. Topics of interest include, but are not limited to, multispectral and hyperspectral imaging, object detection and tracking, SAR and InSAR-based deformation analysis, sensor data fusion, 3D modeling, and applications of AI in sensor networks.

As a Guest Editor and a Professor of data and business analytics with a background in geospatial technologies, I aim to highlight interdisciplinary research bridging the fields of image processing, data analytics, and sensor integration. We encourage submissions from academic researchers, industry practitioners, and interdisciplinary teams that push the boundaries of how sensor data are collected, analyzed, and applied in dynamic environments.

Topics of interest that would be suitable for inclusion in this Special Issue include the following:

  1. Remote sensing and Earth observation;
  2. SAR and InSAR for deformation monitoring;
  3. Sensor fusion and multimodal data integration;
  4. Computer vision in industrial and smart systems;
  5. AI and machine learning in image processing;
  6. Geospatial intelligence and GIS-based image analysis;
  7. Medical and biomedical imaging systems;
  8. Autonomous systems and smart surveillance.

Dr. Mahmut Çavur
Guest Editor

Dr. Wendy Zhou
Co-Guest Editor

Manuscript Submission Information

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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. Electronics 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 2400 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

  • image processing
  • sensor systems
  • remote sensing
  • geographic information systems (GISs)

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Published Papers (2 papers)

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Research

22 pages, 5509 KB  
Article
A Novel Automatic Detection and Positioning Strategy for Buried Cylindrical Objects Based on B-Scan GPR Images
by Yubao Liu, Zhenda Zeng, Hang Ye, Xinyu Sun, Zhiqiang Zou and Dongguo Zhou
Electronics 2025, 14(24), 4799; https://doi.org/10.3390/electronics14244799 - 5 Dec 2025
Viewed by 731
Abstract
This paper presents DeepMask-GPR, a novel deep learning framework for automatic detection and geometric estimation of buried cylindrical objects in ground-penetrating radar (GPR) B-scan images. Built upon Mask R-CNN, the proposed method integrates hyperbola detection, apex localization, and real-world coordinate mapping in an [...] Read more.
This paper presents DeepMask-GPR, a novel deep learning framework for automatic detection and geometric estimation of buried cylindrical objects in ground-penetrating radar (GPR) B-scan images. Built upon Mask R-CNN, the proposed method integrates hyperbola detection, apex localization, and real-world coordinate mapping in an end-to-end architecture. A curvature-enhanced dual-channel input improves the visibility of weak hyperbolic patterns, while a quadratic regression loss guides the network to recover precise geometric parameters. DeepMask-GPR eliminates the need for raw signal data or manual post-processing, enabling robust and scalable deployment in field scenarios. On two public datasets, DeepMask-GPR achieves consistently higher TPR/IoU for spatial localization than baselines. On an in-house B-scan set, it attains low MAE/RMSE for radius estimation. Full article
(This article belongs to the Special Issue Applications of Image Processing and Sensor Systems)
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28 pages, 29247 KB  
Article
Channel Capacity Analysis of Partial-CSI SWIPT Opportunistic Amplify-and-Forward (OAF) Relaying over Rayleigh Fading
by Kyunbyoung Ko and Seokil Song
Electronics 2025, 14(19), 3791; https://doi.org/10.3390/electronics14193791 - 24 Sep 2025
Viewed by 568
Abstract
This paper presents an analytical framework for the channel capacity evaluation of simultaneous wireless information and power transfer (SWIPT)-enabled opportunistic amplify-and-forward (OAF) relaying systems over Rayleigh fading channels. For the SWIPT, we employ a power splitter (PS) at the relay, which splits the [...] Read more.
This paper presents an analytical framework for the channel capacity evaluation of simultaneous wireless information and power transfer (SWIPT)-enabled opportunistic amplify-and-forward (OAF) relaying systems over Rayleigh fading channels. For the SWIPT, we employ a power splitter (PS) at the relay, which splits the received signal into the information transmission and the energy-harvesting parts. By modeling the partial channel state information (P-CSI)-based SWIPT OAF system as an equivalent non-SWIPT OAF configuration, a semi-lower bound and a new upper bound on the ergodic channel capacity are derived. A refined approximation is then obtained by averaging these bounds, yielding a simple yet accurate analytical estimate of the true capacity. Simulation results confirm that the proposed approximations closely track the actual performance across a wide range of signal-to-noise ratios (SNRs) and relay configurations. They further demonstrate that SR-based relay selection provides higher capacity than RD-based selection, primarily due to its direct influence on energy harvesting efficiency at the relay. In addition, diversity advantages manifest mainly as SNR improvements, rather than as gains in diversity order. The proposed framework thus serves as a practical and insightful tool for the capacity analysis and design of SWIPT-enabled cooperative networks, with direct relevance to energy-constrained Internet of Things (IoT) and wireless sensor applications. Full article
(This article belongs to the Special Issue Applications of Image Processing and Sensor Systems)
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