Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Image fusion using a multi-level image decomposition and fusion method

Not Accessible

Your library or personal account may give you access

Abstract

In recent years, image fusion has emerged as an important research field due to its various applications. Images acquired by different sensors have significant differences in feature representation due to the different imaging principles. Taking visible and infrared image fusion as an example, visible images contain abundant texture details with high spatial resolution. In contrast, infrared images can obtain clear target contour information according to the principle of thermal radiation, and work well in all day/night and all weather conditions. Most existing methods employ the same feature extraction algorithm to get the feature information from visible and infrared images, ignoring the differences among these images. Thus, this paper proposes what we believe to be a novel fusion method based on a multi-level image decomposition method and deep learning fusion strategy for multi-type images. In image decomposition, we not only utilize a multi-level extended approximate low-rank projection matrix learning decomposition method to extract salient feature information from both visible and infrared images, but also apply a multi-level guide filter decomposition method to obtain texture information in visible images. In image fusion, a novel fusion strategy based on a pretrained ResNet50 network is presented to fuse multi-level feature information from both visible and infrared images into corresponding multi-level fused feature information, so as to improve the quality of the final fused image. The proposed method is evaluated subjectively and objectively in a large number of experiments. The experimental results demonstrate that the proposed method exhibits better fusion performance than other existing methods.

© 2021 Optical Society of America

Full Article  |  PDF Article
More Like This
Infrared and visible image perceptive fusion through multi-level Gaussian curvature filtering image decomposition

Wei Tan, Huixin Zhou, Jiangluqi Song, Huan Li, Yue Yu, and Juan Du
Appl. Opt. 58(12) 3064-3073 (2019)

Infrared and visible image fusion algorithm based on a cross-layer densely connected convolutional network

Ruixing Yu, Weiyu Chen, and Bing Zhu
Appl. Opt. 61(11) 3107-3114 (2022)

References

You do not have subscription access to this journal. Citation lists with outbound citation links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Data Availability

Test image data is available in Ref. [38]. Other data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.

38. A. Toet, “TNO image fusion dataset,” figshare, 2014, https://doi.org/10.6084/m9.figshare.1008029.v1.

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Figures (10)

You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Tables (7)

You do not have subscription access to this journal. Article tables are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Equations (10)

You do not have subscription access to this journal. Equations are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Metrics

Select as filters


Select Topics Cancel
© Copyright 2022 | Optica Publishing Group. All Rights Reserved