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Morphological center operator based infrared and visible image fusion through correlation coefficient

机译:基于相关系数的基于形态学中心算子的红外与可见光图像融合

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摘要

It is important to well maintain the information of infrared (IR) and visible images, including image regions and details, in a fusion image. To be effective for fusion, an algorithm for fusion IR and visible images based on the morphological center operator through feature extraction and correlation coefficient is given. This paper utilizes the contrast enlargement strategy for fusion. Firstly, the morphological center or anti-center operator identifies the bright and dim features of the IR and visible images, and these identified features are used for fusion based on the correlation coefficient. Secondly, the multi-scale morphological theory is employed to extract the multi-scale features through the correlation coefficient based strategy to form the final fusion features. Finally, the extracted final fusion features are combined to form the final fusion image by utilizing the contrast enlargement strategy. Because of the effectively feature identifying by the morphological center and anti-center operators, the proposed algorithm has good performance for IR and visible image fusion. Experiments on different IR and visible images verified that the proposed algorithm performed effectively. (C) 2016 Elsevier B.V. All rights reserved.
机译:重要的是在融合图像中很好地保持红外(IR)和可见图像的信息,包括图像区域和细节。为了有效地进行融合,提出了一种基于形态学中心算子的特征提取和相关系数融合的红外与可见图像融合算法。本文利用对比度放大策略进行融合。首先,形态中心或反中心算子识别出红外和可见图像的明亮和暗淡特征,并将这些识别出的特征用于基于相关系数的融合。其次,采用多尺度形态学理论,通过基于相关系数的策略提取多尺度特征,形成最终的融合特征。最后,利用对比度放大策略将提取出的最终融合特征进行合并,形成最终融合图像。由于形态学中心和反中心算子对特征的有效识别,该算法在红外和可见光图像融合方面具有良好的性能。在不同的红外和可见光图像上的实验证明了该算法的有效性。 (C)2016 Elsevier B.V.保留所有权利。

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