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Improved Image Fusion Method Based on NSCT and Accelerated NMF

机译:基于NSCT和加速NMF的改进图像融合方法

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摘要

In order to improve algorithm efficiency and performance, a technique for image fusion based on the Non-subsampled Contourlet Transform (NSCT) domain and an Accelerated Non-negative Matrix Factorization (ANMF)-based algorithm is proposed in this paper. Firstly, the registered source images are decomposed in multi-scale and multi-direction using the NSCT method. Then, the ANMF algorithm is executed on low-frequency sub-images to get the low-pass coefficients. The low frequency fused image can be generated faster in that the update rules for W and H are optimized and less iterations are needed. In addition, the Neighborhood Homogeneous Measurement (NHM) rule is performed on the high-frequency part to achieve the band-pass coefficients. Finally, the ultimate fused image is obtained by integrating all sub-images with the inverse NSCT. The simulated experiments prove that our method indeed promotes performance when compared to PCA, NSCT-based, NMF-based and weighted NMF-based algorithms.
机译:为了提高算法的效率和性能,提出了一种基于非下采样轮廓波变换(NSCT)域和基于加速非负矩阵分解(ANMF)的图像融合技术。首先,使用NSCT方法在多尺度和多方向上分解配准的源图像。然后,对低频子图像执行ANMF算法以获得低通系数。通过优化W和H的更新规则,并减少迭代次数,可以更快地生成低频融合图像。另外,对高频部分执行邻域同质测量(NHM)规则以实现带通系数。最后,通过将所有子图像与反NSCT集成在一起,获得最终的融合图像。仿真实验证明,与PCA,基于NSCT,基于NMF和基于加权NMF的算法相比,我们的方法确实提高了性能。

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