Dr. Xueyan Gao Profile

Dr. Xueyan Gao

at Tianjin Univ

SPIE Involvement:

Author

Publications (1)

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

SPIE Journal Paper | 29 July 2022

DAFuse: a fusion for infrared and visible images based on generative adversarial network

Xueyan Gao, Shiguang Liu

JEI, Vol. 31, Issue 04, 043023, (July 2022) https://doi.org/10.1117/12.10.1117/1.JEI.31.4.043023

KEYWORDS: Image fusion, Infrared imaging, Infrared radiation, Visible radiation, Feature extraction, Visualization, Network architectures, Convolution, Visual system, Information fusion

Read Abstract +

Infrared and visible image fusion is a popular research hotspot in the field of image processing. However, the existing fusion methods still have some limitations, such as insufficient use of intermediate information and inability to focus on features that are meaningful for fusion. To solve these problems, we propose an infrared and visible image fusion method based on generative adversarial networks with dense connection and attention mechanism (DAFuse). Since infrared and visible image are different modalities, we design two branches to extract the features in infrared and visible image, respectively. To make full use of the features extracted from the middle layer and make the model focus on useful information, we introduce the dense block, channel attention mechanism, and spatial attention mechanism into the generator. The self-attention model is incorporated into the discriminator. The proposed method not only retains rich texture detail features and sufficient contrast information but also conforms to human visual perception. Extensive qualitative and quantitative experimental results show that the proposed method has better performance in visual perception and quantitative evaluation than the existing state-of-the-art methods.

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