基于形态学分割的显著红外目标与可见光图像融合

Pawanjot Kaur, Harbinder Singh, Vinay Kumar
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引用次数: 1

摘要

通过图像融合,可以将同一场景的不同图像中的大量信息整合到单个图像中,可用于人类可视化和计算机视觉等图像处理任务。提出了一种基于形态学运算的单分辨率加权平均图像融合方法。为了从红外图像中选择显著的红外目标细节和从可见光图像中选择空间细节信息,对输入图像进行形态学运算,进行权重图计算。该方法在很大程度上保留了空间信息,融合后的图像能够很好地显示红外目标。实验结果证明了形态学操作在基于加权平均的红外图像与可见光图像融合中的有效性。
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Salient infrared target and visible image fusion based on morphological segmentation
The considerable information from different images of same scene can be integrated into single image by using image fusion which is worthy for human visualization and computer vision and other image-processing tasks. In this paper, single resolution weighted average image fusion approach based on morphological operations is proposed. To select salient infrared targets details from infrared imagery and spatial detailed information from visible imagery, the morphological operation are applied on input images for weight map computation. By adopting the proposed method, spatial information is mostly preserved and infrared targets can be easily visualized in the resulting fused images. Experimental results are demonstrated to support the validity of morphological operations for weighted average based fusion of infrared image and visible image.
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