1) complex contourlet packet transform(CCPT)
复轮廓波包变换(CCPT)
2) complex contourlet transform
复轮廓波变换
1.
In order to overcome the aliasing phenomenon commonly existing in real contourlet transform image denoising,some characters of complex contourlet transform whose structure is a cascading of dual tree complex wavelet and directional filter banks are discussed.
为了克服实轮廓波图像消噪后广泛存在的混叠现象,研究了基于双树复小波级联方向滤波器架构的复轮廓波变换图像消噪的若干性质,证明了对于高斯白噪声图像,该变换具有更好的分割能力和抑制能力,并在此基础上提出了一种基于该变换的图像消噪算法。
3) Contourlet transform
轮廓波变换
1.
De-nosing capability of a filter based on contourlet transform;
基于轮廓波变换的滤波器消噪性能
2.
Mapping based complex contourlet transform texture image retrieval system
基于映射的复轮廓波变换纹理图像检索系统
3.
Sample noise response method used to determine subband threshold factors of contourlet transform denoising is proposed.
提出了适用于轮廓波变换消噪中确定子带阈值收敛因子的样本噪声响应法。
4) nonsubsampled complex contourlet transform(NSCCT)
非抽样复轮廓波变换(NSCCT)
1.
A novel nonsubsampled complex contourlet transform(NSCCT)is constructed by combining the two dimensional dual-tree complex wavelet transform(DT-CWT)and nonsubsampled directional filter bank(NSDFB).
将二维双树复小波变换(DT-CWT)与非抽样方向滤波器组(NSDFB)相结合,构造一种新的非抽样复轮廓波变换(NSCCT),并对其平移不变性作了相应证明。
5) wavelet transform profilometry
小波变换轮廓术
1.
Analyzing wavelet transform profilometry in the restraining CCD nonlinear characteristic
小波变换轮廓术抑制CCD非线性的分析
2.
By the wavelet transform profilometry,the height distribution of an object can be obtained by calculating the wavelet coefficient of the deformed fringe pattern at the "ridge" position even there are some frequency overlaps between the fundamental frequency and the higher-order spectra.
结果表明,只有在无周期内瞬时频谱混叠,即任意位置处物体瞬时高度变化满足h/xx=b<1/3条件时,和不存在抽样引起的周期间瞬时频谱混叠的抽样条件下(即一个周期内的抽样点数m≥4时),小波变换轮廓术才能正确恢复被测物体的三维面型。
6) basic contourlet transform
基本轮廓波变换
1.
Referring to the low retrieval rate of basic contourlet transform,a Non-subsampled Contourlet Transform (NSCT) texture image retrieval system is proposed.
针对基本轮廓波变换纹理检索系统检索率较低的问题,提出了一种无下采样轮廓波变换(NSCT)纹理图像检索系统。
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