ABSTRACT The ideal fusion of infrared and visible images is to preserve the details of the visible image as much as possible and superimpose important highlights of the infrared image on the visible image. Therefore, this paper proposes a multiple differential gradient method (MDG) that fuses the infrared image with the difference image of the visible light image and the gradient image of the infrared image. First, an image with comprehensive information is obtained through the difference between the infrared image and the visible image, and it is fused with the suppressed visible image. The new image obtained is then fused with the divergent image of the infrared gradient. Finally, the gray value of the visible image is compared with the new image, and the point with the larger gray value is selected to be fused into the new image. The result is better than most classical algorithms.

中文翻译：

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基于多重差分梯度的可见光和红外图像融合

摘要 红外与可见光图像的理想融合是尽可能保留可见光图像的细节，将红外图像的重要亮点叠加在可见光图像上。因此，本文提出了一种将红外图像与可见光图像的差分图像和红外图像的梯度图像融合在一起的多重差分梯度法（MDG）。首先，通过红外图像和可见光图像的差异得到信息全面的图像，并与抑制后的可见光图像进行融合。然后将获得的新图像与红外梯度的发散图像融合。最后，将可见图像的灰度值与新图像进行比较，选择灰度值较大的点融合到新图像中。