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Survey Paper on Image Fusion using Hybrid Non-subsampled Contourlet Transform and Neural Network

机译:用混合非分布轮廓变换和神经网络测量纸上的图像融合

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This paper is review on image fusion for different technique i.e. Non-subsampled Contourlet Transform (NSCT) and Neural Network (NN). NSCT is the pyramid structure and gives the multiscale feature of the image. NSCT used to directional filtering structure and used to filter bank. Neural network is a progression of calculations that tries to perceive fundamental connections in a bunch of information through an interaction that impersonates the manner in which the human mind works. The implemented algorithm will applied to MRI image and with the help of NN to calculated accuracy. The previous algorithm was work of different technique i.e. principal component analysis, discrete wavelet transorm and curvelet transform. The implemented algorithm will implement MATLAB software and calculate mean square error and peak signal to noise ratio.
机译:本文是关于不同技术的图像融合的综述,即非已撤销轮廓变换(NSCT)和神经网络(NN)。 NSCT是金字塔结构,并提供图像的多尺度特征。 NSCT用于定向滤波结构并用于过滤银行。 神经网络是通过互动的互动来试图在一堆信息中察觉到基本联系的计算进展。 实现的算法将应用于MRI图像,并且在NN以计算精度的帮助下。 先前的算法是不同技术的工作,即主成分分析,离散小波转机和Curvelet变换。 实现的算法将实现MATLAB软件并计算均方误差和峰值信号到噪声比。

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