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Remote sensing image fusion based on orientation information in nonsubsampled contourlet transform domain

机译:基于非管道采样轮廓变换域的方向信息的遥感图像融合

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For improving the traditional fusion algorithm quality and detail information, a fusion algorithm based on orientation information and pulse coupled neural networks (PCNN) in nonsubsampled contourlet transform (NSCT) domain has been proposed. Firstly, convert the multispectral (MS) image into intensity hue saturation (IHS) colour space. Match the histogram of panchromatic (PAN) image to the histogram of I component of MS image. Then decompose the I component and matched PAN image by NSCT, and apply orientation information combined PCNN fusion rules to NSCT coefficients. Reconstruct the fused I component by inverse NSCT transform. Finally, convert the fused MS image back to RGB space. A large number of experiment results have been done to prove that the method proposed in this paper gives better results than the other techniques used.
机译:为了改善传统的融合算法质量和细节信息,已经提出了一种基于方向信息和脉冲耦合神经网络(PCNN)的非频率耦合在非比普普莱特·转换变换(NSCT)域的融合算法。 首先,将多光谱(MS)图像转换为强度色调饱和度(IHS)颜色空间。 将Panchromatic(PAN)图像的直方图与MS图像的I分量的直方图匹配。 然后通过NSCT分解I分量和匹配的PAN图像,并将方向信息组合到NSCT系数组合给NSCT系数。 通过逆NSCT变换重建熔化的I组件。 最后,将熔融MS图像转换回RGB空间。 已经完成了大量的实验结果来证明本文提出的方法具有比所用技术的更好结果。

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