基于NSCT和PCNN的SAR/红外图像融合方法

Wan Luo, Hongbo Zhang, Jing Ding
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引用次数: 1

摘要

为了提高SAR图像与红外图像融合图像的质量,提出了一种基于非下采样轮廓波变换(NSCT)和脉冲耦合神经网络(PCNN)的SAR/红外图像融合新方法。该方法首先通过NSCT分别对SAR图像和红外图像进行分解;然后将PCNN作为该方法的融合规则。最后,通过NSCT反变换得到融合图像。结果表明,与其他融合方法相比,本文所提出的融合方法可以获得信息丰富、对比度强的高分辨率融合图像。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A SAR/Infrared Image Fusion Method Based on NSCT and PCNN
In order to improve the quality of the fusion image between SAR image and infrared image, a novel SAR/infrared image fusion method based on non-subsampled contourlet transform (NSCT) and pulse coupled neural network (PCNN) is proposed. Firstly, this method decomposes the SAR image and infrared image respectively via NSCT. Then PCNN is used as the fusion rule of our method. Finally, the fusion image is obtained by taking the inverse NSCT transform. The results indicate that, compared with other fusion methods, higher resolution fusion image with rich information and strong contrast can be get by the method proposed in this paper.
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