In this paper, the idea of regression model is adopted to complete the fusion of multi-focus images through an end-to-end generative adversarial network (GAN). In the generator part, image features are extracted through multi-branch connection and dense connection technology. In the process of extracting high-dimensional image features, the ECA module is embedded to improve the capability of network. In the discriminator part, the idea of relative GAN is used to predict the relative authenticity between images. Due to the idea and reasonable network construction, the method proposed in this paper can obtain good results of image fusion. And the experimental results demonstrate that the one can also obtain fine results in objective evaluation, which is better than the compared algorithms.
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.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
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.