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Applied Sciences
Special Issues
Recent Advances and Application of Image Processing
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Recent Advances and Application of Image Processing

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

Deadline for manuscript submissions: 30 June 2024 | Viewed by 1455

Special Issue Editors

Dr. Hang Chen

E-Mail Website
Guest Editor
1. CNRS, CRAN UMR 7039, Universitéde Lorraine, 54000 Nancy, France
2. School of Space Information, Space Engineering University, Beijing 101400, China
Interests: electronic engineering; computer security and reliability; image security; hyperspectral image processing
Prof. Dr. Camel Tanougast

E-Mail Website
Guest Editor
Laboratoire Conception Optimisation et Modélisation des Systémes, Université de Lorraine, 57070 Metz, France
Interests: communication engineering; electronic engineering; computer security and reliability; image security; computer communications (networks)

Special Issue Information

Dear Colleagues,

In recent years, image processing technology has developed rapidly. Advanced technologies such as image recognition, image segmentation, object detection, and 3D image reconstruction have been thoroughly researched and applied to various emerging industries, such as autonomous driving, medical assistance, and security surveillance. In particular, the advancement in deep learning technology has overcome the image processing requirement of image content interpretability, which has greatly expanded the application scenarios of image processing technology. Based on the development and application of these new technologies in image processing, many challenges in previous image processing techniques have recently been solved. Research into new image processing techniques has brought about new improvements in the application scenarios of image processing.

This Special Issue aims to provide a communication platform for latest progress in relation to digital images. We are looking forward to publishing the latest original research results and review articles related to the topic of this Special Issue.

Dr. Hang Chen
Prof. Dr. Camel Tanougast
Guest Editors

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. Applied Sciences 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/video-processing technologies in emerging industries
  • image/video-processing technologies in remote surgery
  • image/video-processing technologies in autopilot
  • image/video processing technologies in virtual reality
  • image/video-processing technologies in machine vision
  • industrial production and imaging applications
  • machine learning in image processing
  • emerging multimedia

Published Papers (2 papers)

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Research

16 pages, 3475 KiB  
Article
Agile Attitude Maneuver Control of Micro-Satellites for Multi-Target Observation Based on Piecewise Power Reaching Law and Variable-Structure Sliding Mode Control
by Xinyan Yang, Yurong Liao, Lei Li and Zhaoming Li
Appl. Sci. 2024, 14(2), 797; https://doi.org/10.3390/app14020797 - 17 Jan 2024
Viewed by 438
Abstract
This paper addresses the issue of agile attitude maneuver control for low-Earth-orbit satellites during short arc segments for multi-target observations. Specifically, a configuration design for Control Moment Gyroscopes (CMGs) and a hybrid control law are provided. The control law is adept at avoiding [...] Read more.
This paper addresses the issue of agile attitude maneuver control for low-Earth-orbit satellites during short arc segments for multi-target observations. Specifically, a configuration design for Control Moment Gyroscopes (CMGs) and a hybrid control law are provided. The control law is adept at avoiding singularities and escaping singular planes. Subsequently, an optimal time-based attitude maneuver path-planning method is presented, rooted in the relationship between Euler angles/axis and quaternions. Furthermore, a novel satellite attitude maneuver controller is developed based on a piecewise power-reaching law for variable structure sliding mode control. The paper theoretically demonstrates that the proposed piecewise power reaching law possesses two favorable properties regarding convergence time. On the other hand, the designed reaching law maintains continuity at all stages, theoretically eliminating buffeting. The simulation results demonstrate that the proposed controller achieves an Euler angle control precision of ±0.03° and angular velocity accuracy of ±0.15°/s, fulfilling the demands of multi-objective observational tasks. Compared to conventional power reaching law controllers, the convergence time is reduced by 3 s, and Euler angle accuracy is improved by 70%. This underscores the effectiveness of the proposed algorithm. Full article
(This article belongs to the Special Issue Recent Advances and Application of Image Processing)
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18 pages, 2045 KiB  
Article
Iterated Orthogonal Simplex Cubature Kalman Filter and Its Applications in Target Tracking
by Zhaoming Li, Xinyan Yang, Lei Li and Hang Chen
Appl. Sci. 2024, 14(1), 392; https://doi.org/10.3390/app14010392 - 31 Dec 2023
Cited by 1 | Viewed by 605
Abstract
In order to increase a nonlinear system’s state estimate precision, an iterated orthogonal simplex cubature Kalman filter (IOSCKF) is presented in this study for target tracking. The Gaussian-weighted integral is decomposed into a spherical integral and a radial integral, which are approximated using [...] Read more.
In order to increase a nonlinear system’s state estimate precision, an iterated orthogonal simplex cubature Kalman filter (IOSCKF) is presented in this study for target tracking. The Gaussian-weighted integral is decomposed into a spherical integral and a radial integral, which are approximated using the spherical simplex-radial rule and second-order Gauss–Laguerre quadrature rule, respectively, and result in the novel simplex cubature rule. To decrease the high-order error terms, cubature points with appropriate weights are taken from the cubature rule and processed using the provided orthogonal matrix. The structure supporting the nonlinear Kalman filter incorporates the altered points and weights and the calculation steps; from this, the updated time and measurement can be inferred. The Gauss–Newton iteration is employed repeatedly to adjust the measurement update until the termination condition is met and the IOSCKF is attained. The proposed algorithms are applied in target tracking, including CV target tracking and spacecraft orbit tracking, and the simulation results reveal that the IOSCKF can achieve higher accuracy compared to the CKF, SCKF, and OSCKF. In spacecraft orbit tracking simulation, compared with the SCKF, the position tracking accuracy and velocity tracking accuracy of the OSCKF are increased by 2.21% and 1.94%, respectively, which indicates that the orthogonal transformation can improve the tracking accuracy. Furthermore, compared with the OSCKF, the position tracking accuracy and velocity tracking accuracy of the IOSCKF are increased by 2.71% and 2.97%, respectively, which indicates that the tracking accuracy can be effectively improved by introducing iterative calculation into the measurement equation, thus verifying the effectiveness of the method presented in this paper. Full article
(This article belongs to the Special Issue Recent Advances and Application of Image Processing)
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