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Sensing Technologies in Optical Image Stabilization
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Sensing Technologies in Optical Image Stabilization

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensing and Imaging".

Deadline for manuscript submissions: 31 October 2024 | Viewed by 1656

Special Issue Editor

Dr. Tao Tang

E-Mail Website
Guest Editor
Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, China
Interests: mechanical control system; including inertial stabilization technology; vibration rejections; image-based visual serving system

Special Issue Information

Dear Colleagues,

Optical image stabilization is a key technology to achieve target observation, position and measurement. It is widely used in astronomical observation, space exploration, space communication and other fields. With the development of modern technology, the observed target is more and more distant, and the application scenarios are becoming more and more complex, which puts forward higher requirements for optical image stabilization technologies. Therefore, in order to ensure high-resolution observation, image stabilization technology will face many challenges. Sensing technologies play a vital role in optical image stabilization, which can detect the attitude change in the optical system and the offset of the target position, and provide feedback information for the image stabilization system. Sensors need to have high sensitivity, high dynamic range and stability. Researchers are constantly improving sensor design and performance to meet the challenges brought by the increasing distance of observation targets and the complexity of application scenarios.

This Special Issue invites manuscripts that introduce the recent advances in “Sensing Technologies in Optical Image Stabilization”. All theoretical, numerical, and experimental papers are accepted. Topics include, but are not limited to, the following:

  • Sensor technology trends in image stabilization;
  • Image-based feedback control methods;
  • Active vibration control;
  • Inertial-sensor measurement and control;
  • Adaptive disturbance rejection;
  • Remote target sensing and detection;
  • Dim image detection;
  • Optical signal processing;
  • Tip–tilt mirror technology.

Dr. Tao Tang
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. Sensors 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 2600 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

  • attitude sensors
  • active vibration control
  • image stabilization
  • adaptive disturbance rejection
  • tip–tilt correction

Published Papers (2 papers)

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Research

15 pages, 5743 KiB  
Article
Design and Experimental Study of a Hybrid Micro-Vibration Isolation System Based on a Strain Sensor for High-Precision Space Payloads
by Qiwei Guo, Jian Zhou, Liang Li, Minglong Xu and Guoan Tang
Sensors 2024, 24(5), 1649; https://doi.org/10.3390/s24051649 - 03 Mar 2024
Viewed by 543
Abstract
Micro-vibrations significantly influence the imaging quality and pointing accuracy of high-precision space-borne payloads. To mitigate this issue, vibration isolation technology must be employed to reduce the transmission of micro-vibrations to payloads. In this paper, a novel active–passive hybrid isolation (APHI) system based on [...] Read more.
Micro-vibrations significantly influence the imaging quality and pointing accuracy of high-precision space-borne payloads. To mitigate this issue, vibration isolation technology must be employed to reduce the transmission of micro-vibrations to payloads. In this paper, a novel active–passive hybrid isolation (APHI) system based on a strain sensor is proposed for high-precision space payloads, and corresponding theoretical and experimental studies are implemented. First, a theoretical analysis model of the APHI system is established using a two-degrees-of-freedom system, and an integral control method based on strain sensing is presented. Then, an electromagnetic damper, active piezoelectric actuator, and strain sensor are designed and manufactured. Finally, an APHI experimental system is implemented to validate the effectiveness of electromagnetic damping and strain-sensing active control. Additionally, the control effects of acceleration, displacement, and strain sensors are compared. The results demonstrate that strain sensors can achieve effective active damping control, and the control method based on strain sensors can effectively suppress the payload response while maintaining stability. Both displacement and strain sensors exhibit superior suppression effects compared with the acceleration sensor, with the strain sensor showing greater potential for practical engineering applications than the displacement sensor. Full article
(This article belongs to the Special Issue Sensing Technologies in Optical Image Stabilization)
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15 pages, 5852 KiB  
Article
No-Reference Quality Assessment of Extended Target Adaptive Optics Images Using Deep Neural Network
by Guoqing Gao, Lingxiao Li, Hao Chen, Ning Jiang, Shuqi Li, Qing Bian, Hua Bao and Changhui Rao
Sensors 2024, 24(1), 1; https://doi.org/10.3390/s24010001 - 19 Dec 2023
Viewed by 719
Abstract
This paper proposes a supervised deep neural network model for accomplishing highly efficient image quality assessment (IQA) for adaptive optics (AO) images. The AO imaging systems based on ground-based telescopes suffer from residual atmospheric turbulence, tracking error, and photoelectric noise, which can lead [...] Read more.
This paper proposes a supervised deep neural network model for accomplishing highly efficient image quality assessment (IQA) for adaptive optics (AO) images. The AO imaging systems based on ground-based telescopes suffer from residual atmospheric turbulence, tracking error, and photoelectric noise, which can lead to varying degrees of image degradation, making image processing challenging. Currently, assessing the quality and selecting frames of AO images depend on either traditional IQA methods or manual evaluation by experienced researchers, neither of which is entirely reliable. The proposed network is trained by leveraging the similarity between the point spread function (PSF) of the degraded image and the Airy spot as its supervised training instead of relying on the features of the degraded image itself as a quality label. This approach is reflective of the relationship between the degradation factors of the AO imaging process and the image quality and does not require the analysis of the image’s specific feature or degradation model. The simulation test data show a Spearman’s rank correlation coefficient (SRCC) of 0.97, and our method was also validated using actual acquired AO images. The experimental results indicate that our method is more accurate in evaluating AO image quality compared to traditional IQA methods. Full article
(This article belongs to the Special Issue Sensing Technologies in Optical Image Stabilization)
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