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A fusion method for infrared-visible image and infrared-polarization image based on multi-scale center-surround top-hat transform

机译:基于多尺度中心环绕式顶帽变换的红外可见图像和红外极化图像的融合方法

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摘要

This paper presents a fusion method for infrared-visible image and infrared-polarization image based on multi-scale center-surround top-hat transform which can effectively extract the feature information and detail information of source images. Firstly, the multi-scale bright (dark) feature regions of source images at different scale levels are respectively extracted by multi-scale center-surround top-hat transform. Secondly, the bright (dark) feature regions at different scale levels are refined for eliminating the redundancies by spatial scale. Thirdly, the refined bright (dark) feature regions from different scales are combined into the fused bright (dark) feature regions through adding. Then, a base image is calculated by performing dilation and erosion on the source images with the largest scale outer structure element. Finally, the fusion image is obtained by importing the fused bright and dark features into the base image with a reasonable strategy. Experimental results indicate that the proposed fusion method can obtain state-of-the-art performance in both aspects of objective assessment and subjective visual quality.
机译:本文介绍了基于多尺度中心环绕式顶帽变换的红外可见图像和红外偏振图像的融合方法,其可以有效地提取源图像的​​特征信息和详细信息。首先,分别通过多尺度中心环绕式顶部帽子变换来提取不同比例级别的源图像的多尺度明亮(暗)特征区域。其次,通过空间尺度来精制不同刻度水平的明亮(暗)特征区域,以消除冗余。第三,通过添加,将来自不同尺度的精致明亮(暗)特征区域组合成熔融明亮(暗)特征区域。然后,通过在具有最大刻度外部结构元件的源图像上执行扩张和侵蚀来计算基础图像。最后,通过以合理的策略导入基础图像中的融合明亮和暗特征来获得融合图像。实验结果表明,拟议的融合方法可以在客观评估和主观视觉质量方面获得最先进的性能。

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