关键词: 图像融合, 非下采样Shearlet变换（NSST）, 增强背景检测的显著性优化（RBD）, 局部拉普拉斯滤波（LLF）, S曲线变换

Abstract: An image fusion method based on LLF and RBD is proposed. In order to make full use of the target information of the infrared image and the detail information of the visible image, local Laplacian filters are used to smooth the infrared image and enhance the visible image. On this basis, RBD is used to process the infrared image for detecting the target better. In addition, in order to enhance the target information, reduce the background interference, the result of RBD is transformed by S curve. Then, the infrared and visible images are decomposed into high frequency and low frequency components by NSST. Finally, the low-frequency components are fused with saliency map obtained by S transform and the high-frequency components are fused with the rule of large absolute value. The experimental results show that the fusion method can get the fusion image of the infrared target highlight and the detail enhancement.

Key words: image fusion, Nonsubsampled Shearlet Transformation（NSST）, saliency optimization from Robust Background Detection（RBD）, Local Laplacian Filters（LLF）, transformation of S curves