A Multiscale Morphological Method for Visible and Infrared Images Fusion

Julio César Mello Román, José Luis Vázquez Noguera, H. Legal-Ayala
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Abstract

Infrared images (IR) help us to detect hidden targets in the environment, according to the radiation they emit. These work well on the day, at night and in weather conditions such as rain or fog. At the same time, visible images (VIS) provide us with good details of the scenes, which are better perceived by the human eye. Therefore, the fusion of an infrared image and a visible image of the same scene is very useful. In this paper, we propose a fusion method of visible and infrared images using a multiscale morphological approach. First, the base image is generated through the fusion of the two source images. Second, multiple bright and dark features are extracted from each source image by the top-hat transform. Third, the multiple bright and dark scales of the source images are fused. Finally, the fusion of the visible and infrared images is obtained by adding to the base image the maximum values obtained in the previous step. The results show that the proposed method is competitive compared to state-of-the-art methods in terms of contrast, brightness, texture and spatial information.
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可见光与红外图像融合的多尺度形态学方法
红外图像(IR)根据它们发出的辐射帮助我们探测环境中隐藏的目标。这些在白天、晚上以及下雨或大雾等天气条件下都能很好地工作。同时,可视图像(VIS)为我们提供了场景的良好细节,这些细节更容易被人眼感知。因此,对同一场景的红外图像和可见光图像进行融合是非常有用的。本文提出了一种基于多尺度形态学的可见光和红外图像融合方法。首先,将两幅源图像融合生成基图像。其次,通过顶帽变换从每个源图像中提取多个明暗特征;第三,对源图像的多个明暗尺度进行融合。最后,将上一步得到的最大值加到基图上,实现可见光图像与红外图像的融合。结果表明,该方法在对比度、亮度、纹理和空间信息等方面优于现有方法。
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