This article proposes to utilize the dual-tree complex wavelet transformation to the core image denoising, and good effect is obtained.
岩心图像的去噪是后续的目标检测与定量分析的关键。
The image denoising method is proposed based on dual tree complex wavelet transform, which can do better both in features preserving and noise removing.
将对偶树复小波变换应用于图像去噪，可以更好地表示图像的边缘和纹理特征，从而得到较小波更好的去噪效果。
A new locally adaptive image denoising method, which exploits the intra-scale and inter-scale dependency in the dual-tree complex wavelet domain, is presented.
充分利用二元树复数小波域内系数尺度间和尺度内的统计依赖关系，提出了一种新的局部自适应图像去噪方法。
The results show that the EWC threshold method of complex wavelet transform can effectively suppress the periodic narrowband interference from GIS UHF PD signals.
研究结果表明：基于EWC阈值法的复小波变换能够有效地抑制GIS特高频PD信号中的周期性窄带干扰。
The merit of both shift invariance and directional selectivity enables the complex wavelet to overcome the artifacts in the discrete orthonormal wavelet denoising.
由于复数小波具备平移不变性和方向选择性等优点，使得它在图像去噪中可以克服离散正交小波变换去噪中存在的毛刺现象。
In order to enlarge the difference of fault line and normal line, the complex wavelet pocket band entropy of all sub-frequency bands in feature band is made product.
为了扩大故障线路与正常线路的差别，对特征频带内各子频带的频带熵作积处理，得到了复小波包特征频带复合熵线路特征量化准则。
We propose a MC-CDMA system based on the optimized multiband complex wavelet transform (MBCWT), investigate the system performance in multipath Rayleigh fading channel.
提出一种基于优化多带复小波变换的MC-CDMA系统，研究了其在多径瑞利衰落下的性能。
A novel method is proposed in this paper by research on complex wavelet, in which phase information of complex wavelet transforms is used to detect frequency and harmonics.
本文通过对复小波的研究发现复小波变换的相位信息能用于频率检测和谐波分析，提出了基于复小波变换相位信息的频率和谐波检测新算法。
Secondly, using locally variance estimation, a locally adaptive image-denoising algorithm was presented. Also this algorithm could be applied to the complex wavelet domain.
在实验中，将该算法分别应用到实值离散小波变换域和双树复数小波变换域，并和隐马尔科夫模型的去噪方法做了比较分析。
Finally, based on the work of above, proposed a method of description and extraction image color and texture features in the dual tree complex wavelet transformation domain.
最后，在上面工作的基础上，提出了基于对偶数复小波域的图像的颜色和纹理特征的描述和提取方法。
Because complex wavelet transforms can exactly identify amplitude and phase information in signal to be dealt with, they are suitable for detection of fault signals in power system.
复值小波变换能准确分辨出信号中所包含的幅值信息和相位信息，因而，适用于电力系统的故障信号的检测。
Phase information is one of emphasis characters in the power system orthogonal or biorthogonal complex wavelet is strong means to extract phase information in the power system in time.
相位信息是电力系统的一个重要特征，正交或双正交的复小波是实时提取电力系统中相位信息的有力手段。
By comparison with other wavelet functions, trapezoid complex wavelet function has even frequency characteristic, and so trapezoid complex wavelet transform easily catch frequency deviation.
梯形小波函数具有平坦的频率特性，因而梯形小波变换较容易捕捉到信号的频率偏移。
In order to avoid misjudgement in all kinds of fault condition, a criterion is defined that the maximum of complex wavelet pocket band composite entropy divisions the secondary maximum of that.
为了有效避免各种情况下的选线误判，将所有线路的频带复合熵最大值与次最大值之比作为选线依据。
The complex wavelet functions constructed by means of this method have advantages of good performance in frequency localization and better veracity in extracting characteristic parts of signals.
该方法构造的复值小波具有频率局部化性能好、取故障信号特征分量较准确的优点。
Presents a novel texture retrieval approach of medical images based on statistic model by Dual-Tree Complex Wavelet Trans - form (DT-CWT) for the shift sensitivity and poor directionality of DWT.
针对离散小波变换具有平移变化性和弱方向性的特性，本文提出了一种基于双树复小波变换(DT- CWT)统计模型的医学图像纹理检索方法。
The theory of wavelet packet is more complex than the analysis of wavelet, but its means of analysis is more flexible, and has more accurate partial analysis ability.
小波包理论比小波分析更为复杂，但其分析手段更为灵活，具有更为精确的局部分析能力。
The small target detection method of infrared imagery in complex background of sea and sky in studied, and an algorithm based on wavelet analysis and mutual energy combination is presented.
研究复杂背景下红外图像小目标检测问题，提出一种基于小波分析互能量交叉处理的目标检测方法。
Starting from perfect reconstruction filter Banks, the relationship between the wavelet and the filter Banks is analyzed, and the construction of complex discrete orthonormal wavelet is discussed.
从完全重构滤波器组出发，分析了小波与滤波器组之间的关系，讨论了复数离散正交小波的构造。
From this, detection, location and classification of power quality's disturbances are analyzed respectively, by the symmetry complex compactly-supported orthonormal wavelet constructed.
利用所构造的复数正交紧支对称小波，分别研究了电网电能质量扰动的检测、定位与分类问题。
A scene matching algorithm based on complex valued wavelet transform is discussed in this paper. We propose an effective scene matching model based on this algorithm.
讨论了一种基于复数小波变换的景像匹配算法，并以此算法为基础给出了一个高效的景像匹配模型。
The wavelet transform does multi-resolution analysis on the signal which clarifies the electrocardiogram (ECG) signal characteristics to more easily detect the QRS complex.
小波分解对信号做多分辨率分解，可以突出信号的特征信息，便于QRS波群检测。
This paper presents an effective license plate location algorithm, which employs wavelet transformation and intensity moment to extract number plate from the complex-background images.
提出一种基于小波分解和亮度矩的复杂背景下，图像中车牌定位和分割的方法。
The studies include development of generating system of 12-lead synchronous abnormal ECG waveform database, wavelet based QRS complex detection algorism and waveform analysis.
建立了12导联同步心电异常波形数据库生成系统，并在此基础上研究了12导联心电图实时分析与基于小波变换的QRS波自动识别算法。
Compared with the wavelet analysis, the dynamic reference waves are more flexible and effective in extracting the available fault traveling waves in the complex environment with serious noise.
和小波分析法相比，动态的参考波对于在复杂的干扰环境下提取有用的故障波形更加灵活、有效。
Objective To find a new method for ECG autoanalysis of through the combination of energy transform and wavelet decomposition for detecting the characteristic point of QRS complex.
目的使用能量变换与小波分解的联合算法检测心电信号QRS波群的特征点，为心电信号的自动分析提供新的手段。
In this paper, several characteristics of ECG from patients, such as QRS complex and its onset and offset T wave and S-T segment, has been detected using wavelet method.
本课题基于小波理论设计软件算法，提出了模极值线群方法，抽取心电信号中若干具有临床价值的特征：QRS波群组态及其起点和终点、T波、S-T段。
A method using transient frequency based on complex-analytical- wavelet-transform, which combines Hilbert transform with wavelet transform and possesses adaptive analytical ability, is proposed.
建议了一种基于复解析小波变换的瞬时频率分析齿轮故障振动信号的方法。 该方法将希尔伯特变换与小波变换相结合，具有自适应分析能力。
A method using transient frequency based on complex-analytical- wavelet-transform, which combines Hilbert transform with wavelet transform and possesses adaptive analytical ability, is proposed.
建议了一种基于复解析小波变换的瞬时频率分析齿轮故障振动信号的方法。 该方法将希尔伯特变换与小波变换相结合，具有自适应分析能力。
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