An Effective Infrared and Visible Image Fusion Approach via Rolling Guidance Filtering and Gradient Saliency Map

Author:

Li Liangliang12ORCID,Lv Ming3,Jia Zhenhong3,Jin Qingxin4,Liu Minqin5,Chen Liangfu6,Ma Hongbing1ORCID

Affiliation:

1. Department of Electronic Engineering, Tsinghua University, Beijing 100084, China

2. School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China

3. College of Information Science and Engineering, Xinjiang University, Urumqi 830046, China

4. School of Mechanical Engineering, Guangxi University, Nanning 530004, China

5. Institute of Software, Chinese Academy of Sciences, Beijing 100190, China

6. State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

Abstract

To solve problems of brightness and detail information loss in infrared and visible image fusion, an effective infrared and visible image fusion method using rolling guidance filtering and gradient saliency map is proposed in this paper. The rolling guidance filtering is used to decompose the input images into approximate layers and residual layers; the energy attribute fusion model is used to fuse the approximate layers; the gradient saliency map is introduced and the corresponding weight matrices are constructed to perform on residual layers. The fusion image is generated by reconstructing the fused approximate layer sub-image and residual layer sub-images. Experimental results demonstrate the superiority of the proposed infrared and visible image fusion method.

Funder

Beijing National Research Center for Information Science and Technology

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

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