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Infrared and visible image fusion method based on rolling guidance filter and NSST

机译:基于轧制引导滤波器和NSST的红外和可见图像融合方法

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摘要

The rolling guidance filtering (RGF) has a good characteristic which can smooth texture and preserve the edges, and non-subsampled shearlet transform (NSST) has the features of translation invariance and direction selection based on which a new infrared and visible image fusion method is proposed. Firstly, the rolling guidance filter is used to decompose infrared and visible images into the base and detail layers. Then, the NSST is utilized on the base layer to get the high-frequency coefficients and low-frequency coefficients. The fusion of low-frequency coefficients uses visual saliency map as a fusion rule, and the coefficients of the high-frequency subbands use gradient domain guided filtering (GDGF) and improved Laplacian sum to fuse coefficients. Finally, the fusion of the detail layers combines phase congruency and gradient domain guided filtering as the fusion rule. As a result, the proposed method can not only extract the infrared targets, but also fully preserves the background information of the visible images. Experimental results indicate that our method can achieve a superior performance compared with other fusion methods in both subjective and objective assessments.
机译:轧制引导滤波(RGF)具有良好的特性,可以平滑纹理并保持边缘,并且非撤销的Shearlet变换(NSST)具有基于该翻译不变性和方向选择的特征,基于哪种新的红外和可见图像融合方法是建议的。首先,滚动引导滤波器用于将红外和可见图像分解到基座和细节层中。然后,在基础层上使用NSST以获得高频系数和低频系数。低频系数的融合使用视觉显着图作为融合规则,高频子带的系数使用梯度域引导滤波(GDGF)并改进的LAPLACIAN SUM到保险丝系数。最后,细节图层的融合将相变和梯度域引导滤波结合为融合规则。结果,所提出的方法不仅可以提取红外目标,还可以完全保留可见图像的背景信息。实验结果表明,与主体和客观评估中的其他融合方法相比,我们的方法可以实现优越的性能。

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