In order to improve the clarity of image fusion and solve the problem that the image fusion effect is affected by the illumination and weather of visible light, a fusion method of infrared and visible images for night-vision context enhancement is proposed. First, a guided filter is used to enhance the details of the visible image. Then, the enhanced visible and infrared images are decomposed by the curvelet transform. The improved sparse representation is used to fuse the low-frequency part, while the high-frequency part is fused with the parametric adaptation pulse-coupled neural networks. Finally, the fusion result is obtained by inverse transformation of the curvelet transform. The experimental results show that the proposed method has good performance in detail processing, edge protection, and source image information.

中文翻译：

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基于Curvelet变换和导引滤波增强的图像融合方法

为了提高图像融合的清晰度，解决图像融合效果受可见光的光照和天气影响的问题，提出了一种红外与可见光图像融合的夜视上下文增强方法。首先，使用引导滤镜增强可见图像的细节。然后，通过curvelet变换对增强的可见光和红外图像进行分解。改进的稀疏表示用于融合低频部分，而高频部分则与参数自适应脉冲耦合神经网络融合。最后，通过Curvelet变换的逆变换获得融合结果。实验结果表明，该方法在细节处理，边缘保护和源图像信息方面具有良好的性能。