1) singular Radon transform
奇异Radon变换
1.
In 1986, in order to solve Neumann problem on the pseudo-convex domain, Phong and Stein investigated the L~p-boundedness of the singular Radon transform along sub-manifold with nowhere vanishing rotational curvature.
第一章主要考虑带粗糙核的奇异Radon变换在Lebesgue空间上的有界性。
2) singularity of Radon transform
Radon变换的奇性
3) singularities of Radon transform along round curves
沿上半圆Radon变换的奇性
5) Radon transform
Radon变换
1.
Acoustic imaging detection using a Radon transform-based moment invariant;
基于Radon变换的矩不变量在声成像探测中的应用
2.
Feature extraction based on Radon transform for gait recognition;
基于Radon变换的特征提取在步态识别中的应用
3.
Doppler centroid estimation of SAS based on Radon transform;
基于Radon变换的合成孔径声纳多普勒中心估计
6) Radon-Ambiguity transform
Radon-Ambiguity变换
1.
ARM detection and identification technique based on Radon-Ambiguity transform;
基于Radon-Ambiguity变换的反辐射导弹检测识别技术
2.
The time and frequency analyzing method based on Radon-Ambiguity transform(RAT) is firstly used to estimate acceleration of multi-target and make compensation,then separate the multi-target by using frequency domain filtering and estimate Doppler frequency coarsely;Doppler frequency zooming is carried out for the single separated target by way of CZT.
首先用基于Radon-Ambiguity变换(RAT)的时频分析方法估计多个目标的加速度并进行运动补偿,通过频域滤波对多目标进行分离并估计粗略的多普勒频率,然后对分离后的单个目标通过CZT变换进行多普勒频率细化,提高估计精度。
3.
In order to compare the differences between the Wigner-Hough transform(WHT) and Radon-Ambiguity transform(RAT),the expression of input,output signal noise ratio(SNR) and sampling points are deduced basaed on the ergodic property of stationary Gaussian stochastic process,under cases of large sampling points.
为了比较Wigner-Hough变换(WHT)和Radon-Ambiguity变换(RAT)之间的差别,利用平稳高斯随机过程各态遍历特性,推导了RAT在采样点数较多的情况下,采样点数与输入、输出信噪比之间的关系表达式。
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。
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