Dr. Xin Song Profile

Dr. Xin Song

SPIE Involvement:

Author

Publications (2)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 12 December 2024 Paper

A zero-shot image denoising pipeline for space target detection

Sibei Li, Xin Song, Yuxuan Li

Proceedings Volume 13439, 134392O (2024) https://doi.org/10.1117/12.3055346

KEYWORDS: Stars, Image denoising, Denoising, Image processing, Visualization, Telescopes

Read Abstract +

Optical imaging of space targets using ground-based or space-based telescopes is typically affected by complex noise. Due to the sparse features and limited data, the denoising performance of star images is often suboptimal. In this paper, we propose a lightweight zero-shot star image denoising framework featuring an improved 3-layer U-Net backbone, which can efficiently complete the denoising task without a complete dataset. This network extracts feature information through two pair of down-sampling and up-sampling layers, as well as several convolution modules. The spatial attention module is employed to focus on attention regions, enhancing the model efficiency and generalization ability. In the experiments conducted with real star images, the denoising pipeline primarily consists of three steps: image preprocessing, network training and inference. The results demonstrate that our method effectively removes noise from star images and outperforms existing techniques, facilitating the accurate detection and extraction of space targets in subsequent research.

Proceedings Article | 6 May 2024 Paper

Target positioning based on AIS data and optical remote sensing image fusion

Xueyang Wang, Xin Song, Zhenguo Yan, Yun Cheng

Proceedings Volume 13107, 1310729 (2024) https://doi.org/10.1117/12.3029102

KEYWORDS: Image fusion, Data fusion, Remote sensing, Calibration, Ocean optics, Global Positioning System

Read Abstract +

For ocean remote sensing, target positioning over large areas of sea surface can be challenging, and traditional methods that rely on control points data may not be applicable in such cases. AIS data are commonly used as auxiliary data source of ocean remote sensing, which contains a wealth of attribute information of target. High-precision position information for a large number of targets is provided by the AIS equipped with differential GPS. AIS can be used as dynamic control points on the sea surface to contribute to target positioning in remote sensing image, meeting the on-orbit real-time positioning requirements of ocean remote sensing. This paper proposes a method for on-orbit target positioning and identification through the data fusion of optical image and AIS data. Firstly, the target position information provided by AIS is the broadcasted position over a period of time, while remote sensing image provide the instantaneous captured position. Therefore, it is necessary to calibrate the two types of data in terms of time and space. Then, the grid matching algorithm is used to establish the corresponding relationships between the same targets from the two different datasets, thereby achieving data fusion. Finally, target positioning is achieved over large areas of sea surface. In addition, the identification of target can also be facilitated by remote sensing image with the aid of AIS data, enabling precise positioning of abnormal target while obtaining their image information. In this paper, 5-meter resolution Jilin-1 satellite image and AIS data are used as data sources. The results show that, compared with the original data, the positioning error values calculated by this method are between 5-20 meters, with a reduction of over 70% in the RMSE value.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years