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- banlanced multiwavelet 平衡多小波
- The algorithms of decomposition and reconstruction of biorthogonal multiwavelet packets are given finally. 本文的重点是给出了用此小波包进行分解与重构的算法。
- By means of the mathematical properties of CL multiwavelet, the iris texture feature can be presented accurately and primely. 利用CL多小波优良的数学性质,虹膜纹理特征能够被准确完整地表达。
- The biorthogonality property for multivariate biorthogonal multiwavelet packets has been studied. 讨论了高维不可分双正交多小波包的双正交性。
- Finally,the algorithm proposed can also be used to construct the biorthogonal wavelet or multiwavelet. 另外,该算法还可以用于双正交或多小波滤波器的构造,具有很好的可移植性。
- We propose an optimal vector zerotree coding scheme based on multiwavelet transform. 提出一种基于多小波变换的矢量量化零树编码方案。
- A novel image watermarking algorithm which based on Discrete Multiwavelet Transform(DMT) is proposed. 摘要 提出了一种基于离散多小波变换(DMT)的数字图像水印算法。
- Third, dependence between different components of a vector-subimage emerged after multiwavelet transforming an image. 三、图象多小波分解后子图象分量之间的相关性。
- In this paper, a nonlinear multiwavelet transform adaptive threshold value method is proposed to suppress speckle noise. 摘要文章提出了一种新的用于斑点噪声抑制的非线性多小波变换自适应阈值算法。
- Multiwavelet ortho-normal shell expansion is performed on the contour to get several resolution levels and average value. 采用多小波神经网络簇对轮廓壳进行伸展得到数级多分辨率和其平均值;
- Multiwavelet is an extension form wavelet theory, it can offer a more precise way for image analysis than wavelet multi-resolution analysis. 多小波是小波理论的扩展,多小波变换能够为图像分析提供一种比小波多分辨率更加精细的方法。
- The balanced orthogonal multiwavelet has both orthogonal and symmetry.It has higher resolution and better denoising effect than the scalar wavelet. 平衡正交多小波同时满足正交性和对称性,具有比单小波分解更加精确、去噪效果更好的特点。
- A technique for compressing synthetic aperture radar(SAR) image data using multiwavelet transform and prefilter methods is considered. 利用上述特点将多小波变换应用于SAR图像压缩。
- At first utilized the SOT to normalize the multiwavelet coefficients in high frequency band and removed the signal-dependence of the speckle noise. 首先利用SOT对高频子带的多小波系数进行软阈值去噪,滤除相干斑噪声;
- In the end, a simulation software of multispectral remote-sensing images fusion based on multiwavelet analysis is achieved using VC++6.0. 最后;在VC++6.;0下编程实现了基于多小波分析多光谱图像融合的仿真系统。
- Simulation results indicate that this method is effective,multiwavelet neural network converges more rapidly than wavelet neural network. 仿真结果表明,该方法是有效的,而且比小波神经网络方法的收敛速率快。
- The orthogonal prefilter was designed.The experimental results showed that our multiwavelet could perform better than wavelet and GHM multiwavelet in getting rid of noise. 应用该类向量小波去噪,实验结果表明,处理效果好于单小波和GHM向量小波。
- Therefore,the ultrasound medical image is discomposed to multiwavelet domain.Then its coefficients are shrunk by fuzzy clustering with semi-soft threshold for image de-noising. 故对超声图像进行平衡正交多小波分解,然后利用模糊聚类与半软阈值相结合方法对小波系数进行萎缩处理,实现降噪目的。
- Simulation results indicate that the multiwavelet neural network converges more rapidly than wavelet neural network, and avoids the "dimension disaster". 仿真结果表明,多小波神经网络收敛速度比小波神经网络要快得多,有效地解决了“维数灾”问题。
- Throgh fusing two multi-focus images by method based on multiwavelet analysis, we get fused pictures, the method can fuse details of input images successfully. 利用多小波将两幅图像进行融合后得到的融合图像,能够很好地将原图像的细节融合在一起。