Recently, deep learning has become a rapidly developing tool in the field of image fusion. An innovative image fusion method for fusing infrared images and visible-light images is proposed. The backbone network is an autoencoder. Different from previous autoencoders, the information extraction capability of the encoder is enhanced, and the ability to select the most effective channels in the decoder is optimized. First, the features of the source image are extracted during the encoding process. Then, a new effective fusion strategy is designed to fuse these features. Finally, the fused image is reconstructed by the decoder. Compared with the existing fusion methods, the proposed algorithm achieves state-of-the-art performance in both objective evaluation and visual quality.

中文翻译：

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融合红外和可见光图像的有效方法

最近，深度学习已成为图像融合领域中快速发展的工具。提出了一种融合红外图像和可见光图像的创新图像融合方法。骨干网是一个自动编码器。与以前的自动编码器不同，增强了编码器的信息提取能力，并优化了在解码器中选择最有效通道的能力。首先，在编码过程中提取源图像的​​特征。然后，设计了一种新的有效融合策略来融合这些功能。最后，融合图像由解码器重建。与现有的融合方法相比，该算法在客观评估和视觉质量上均达到了最新水平。