Affiliations: [a] College of Electronics and Information Engineering, Sichuan University, Chengdu, Sichuan, China
| [b] School of Aeronautics & Astronautics, Sichuan University, Chengdu, China
| [c] School of Electronic Engineering, Xidian University, Xi’an, China
| [d] Department of Embedded Syetems Engineering, Incheon National University, Incheon, Korea
Correspondence:
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Corresponding author. Lu Lu, College of Electronics and Information Engineering, Sichuan University, Chengdu, Sichuan, 610064, China. E-mail: lulu19900303@126.com.
Abstract: Infrared (IR) and visible (VIS) image fusion technology combines the complementary information of the same scene from IR and VIS imaging sensors to generate a composite image, which is beneficial to post image-processing tasks. In order to achieve good fusion performance, a method by combining rolling guidance filter (RGF) and convolutional sparse representation (CSR) is proposed. In the proposed method, RGF is performed on every pre-registered IR and VIS source images to obtain their detail layers and base layer. Then, the detail layers are fused with a serious of weighted coefficients produced by joint bilateral filer (JBF). The base layer is decomposed into a sub-detail-layer and a sub-base-layer. CSR is applied to fuse the sub-detail-layer and averaging strategy is used to fuse the sub-base-layer. Finally, the fused image is reconstructed by adding the fused detail layer and base layer. Experimental results demonstrate the superiority of our proposed method both in subjective and objective assessment.
