1) Nonsubsampled Contourlet Transform (NSCT)
非下采样Contourlet变换(NSCT)
1.
The image fusion algorithms based on multi-resolution analysis such as Mallat wavelet transform, lifting wavelet transform and nonsubsampled Contourlet transform (NSCT) proposed here to the fusion image are researched.
本文主要针对基于小波分析的像素级图像融合算法进行探索,研究了基于Mallat小波变换、提升小波变换以及非下采样Contourlet变换(NSCT)的像素级图像融合算法。
2) nonsubsampled contourlet transform
无下采样Contourlet变换(NSCT)
3) nonsubsampled contourlet transform(NSCT)
非下采样变换(NSCT)
4) nonsubsampled contourlet transform(NSCT)
非下采样contourlet变换
1.
An image fusion method based on nonsubsampled contourlet transform(NSCT)is presented,which uses the nonsubsampled pyramids(NSP)and the nonsubsampled directional filter banks(NSDFBs)to decompose the source images in a multi-scale and multi-direction way.
摘要:提出了一种基于非下采样contourlet变换(NSCT)的多分辨率图像融合方法,通过非下采样金字塔(NSP)和非下采样方向滤波器组(NSDFB)实现对图像的多尺度多方向分解。
2.
A fusion algorithm based on Nonsubsampled Contourlet Transform(NSCT)and Pulse Coupled Neural Network(PCNN)was proposed.
提出一种基于非下采样contourlet变换(NSCT)与脉冲耦合神经网络(PCNN)的图像融合算法。
3.
This method was to obtain the value of a threshold automatically using the max signal-to-noise ratio and made different directions multiscale products of high frequency coefficient in order to detect edge of SAR images in NonSubsampled Contourlet Transform(NSCT)domain.
该方法利用信噪比最大自动选取阈值,在非下采样Contourlet变换(NSCT)域中,进行不同方向高频系数多尺度乘积以达到SAR图像检测边缘。
5) Nonsubsampled contourlet transform
非下采样Contourlet变换
1.
SAR image despeckling using statistical priors in nonsubsampled contourlet transform domain;
统计先验指导的非下采样Contourlet变换域SAR图像降斑
2.
Image diffusion denoising based on spectral graph theory and nonsubsampled Contourlet transform
基于非下采样Contourlet变换和谱图理论的扩散去噪
3.
Medical image retrieval based on nonsubsampled Contourlet transform and Zernike moments
基于非下采样Contourlet变换和Zernike矩的医学图像检索
6) non-subsampled Contourlet transform
非下采样Contourlet变换
1.
According to the interscale and intrascale dependencies of the coefficients in the non-subsampled Contourlet transform domain,and considering the change of coefficient\'s aggregation with different directional subbands in the same scale,a novel non-subsampled Contourlet transform denoising scheme using the directional property(ADNSCT) is proposed.
依据非下采样Contourlet分解系数尺度内与尺度间的相关性,考虑到相同尺度内不同方向上系数分布的聚集性依赖图像自身发生变化,提出一种利用方向特性实现非下采样Contourlet变换阈值去噪策略。
补充资料：Radon变换和逆Radon变换
Radon变换和逆Radon变换
X线物理学术语。CT重建图像成像的主要理论依据之一。1917年澳大利亚数学家Radon首先论证了通过物体某一平面的投影重建物体该平面两维空间分布的公式。他的公式要求获得沿该平面所有可能的直线的全部投影(无限集合)。所获得的投影集称为Radon变换。由Radon变换进行重建图像的操作则称为逆Radon变换。Radon变换和逆Radon变换对CT成像的意义在于，它从数学原理上证实了通过物体某一断层层面“沿直线衰减分布的投影”重建该层面单位体积，即体素的线性衰减系数两维空间分布的可能性。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条