Multimodal image seamless fusion

Kun Zhan; Lingwen Kong; Bo Liu; Ying He

doi:10.1117/1.JEI.28.2.023027

5 April 2019 Multimodal image seamless fusion

Kun Zhan, Lingwen Kong, Bo Liu, Ying He

Author Affiliations +

Journal of Electronic Imaging, Vol. 28, Issue 2, 023027 (April 2019). https://doi.org/10.1117/1.JEI.28.2.023027

Abstract

An iterative joint bilateral filter is used to obtain a natural weight map. Images from different modalities are merged by a weighted-sum rule in the spatial domain. Saliency maps are determined by the gradient of the pairwise raw images. Comparing the pairwise values of saliency maps, a coarse weight map is attained to determine which pixel is preferred. Since such a coarse weight map obtained by pairwise comparison is not a natural weight map subjectively, i.e., it is inconsistent with human visual system, the weight map is modified by using an iterative joint bilateral filter. With the iterative joint bilateral filter, the weight map becomes natural. We use the refined weight map to obtain the fused image and we seamlessly merge images from different modalities effectively. Experiments were conducted on several pairs of multimodal images to verify the effectiveness and superiority of the proposed image fusion algorithm compared to the state-of-the-art methods.

Citation Download Citation

Kun Zhan, Lingwen Kong, Bo Liu, and Ying He "Multimodal image seamless fusion," Journal of Electronic Imaging 28(2), 023027 (5 April 2019). https://doi.org/10.1117/1.JEI.28.2.023027

Received: 2 October 2018; Accepted: 20 March 2019; Published: 5 April 2019

ACCESS THE FULL ARTICLE

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