Abstract The ideal fusion of the infrared image and visual image should integrate complete bright features of the infrared image, and preserve original visual information of the visual image as much as possible. To this end, we propose a multi-scale decomposition fusion method based on saliency. In particular, the saliency detection and a Gaussian smoothing filter are first employed to decompose source images into salient layers, detail layers and base layers. Then we adopt a nonlinear function to calculate the weight coefficient to fuse salient layers and highlight the target. Subsequently, we use a fusion rule based on phase congruency for fusion of detail layers so that the details could be retained better than the traditional “max-absolute” fusion rule. Experiments show that the proposed method can achieve better fusion effect than the state-of-the-art methods qualitatively and quantitatively. Moreover, for the ill-illumination fused image, in order to get better visual effect, we further propose a contrast enhancement algorithm based on total variation minimization. Experiments show that the proposed method can enhance the contrast and retain details of the source images well.

中文翻译：

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一种基于显着性的红外和可见光图像融合多尺度方法

摘要 红外图像与可见光图像的理想融合应融合红外图像完整的明亮特征，并尽可能保留可见光图像的原始视觉信息。为此，我们提出了一种基于显着性的多尺度分解融合方法。特别是，首先采用显着性检测和高斯平滑滤波器将源图像分解为显着层、细节层和基础层。然后我们采用非线性函数计算权重系数来融合显着层并突出目标。随后，我们使用基于相位一致性的融合规则来融合细节层，这样可以比传统的“最大绝对”融合规则更好地保留细节。实验表明，所提出的方法在定性和定量上都可以达到比最先进的方法更好的融合效果。此外，对于光照不足的融合图像，为了获得更好的视觉效果，我们进一步提出了一种基于总变异最小化的对比度增强算法。实验表明，所提出的方法可以增强对比度并很好地保留源图像的细节。