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Image fusion based on nonsubsampled contourlet transform

机译:基于非管制型轮廓变换的图像融合

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In this work we have presented an image fusion method based on nonsubsampled contourlet transform (NSCT). Nonsubsampled contourlet transform is a multiscale, multidirectional transform with shift-invariance feature. Shift-invariance is a desirable property for image fusion and many other applications of image processing because it leads to several advantages such as removal of pseudo-Gibbs phenomenon, better frequency selectivity, regularity, improved temporal stability and consistency. Here the input images are decomposed by nonsubsampled contourlet transform and then different fusion rules are applied for low and high frequency NSCT coefficients. Finally the fused image is obtained by the inverse transform. To validate the effectiveness of the proposed method, visual and quantitative analysis are also performed. From the obtained results it is clear that the proposed method outperforms other contourlet and wavelet based methods.
机译:在这项工作中,我们介绍了基于非管制型轮廓变换(NSCT)的图像融合方法。 NonsubSampled Contourlet变换是一个多尺寸的多向变换,具有Shift-Invariance功能。 Shift-Invariance是图像融合的理想特性和图像处理的许多其他应用,因为它导致诸如去除伪GIBB现象,更好的频率选择性,规律性,提高的时间稳定性和一致性等优点。这里,输入图像由非管制的轮廓变换分解,然后应用于低频和高频NSCT系数的不同融合规则。最后,通过逆变换获得熔融图像。为了验证所提出的方法的有效性,还执行视觉和定量分析。从所得结果中显然,所提出的方法优于其他Contourlet和基于小波的方法。

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