该变换引入了各向异性分解方式，由此得到的小波基在各个方向上尺度可以不同，并具有更好的方向性。
By introducing anisotropic decomposition into the transform, the associated wavelet bases may have different sizes in different dimensions, and better directivity.
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。
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.
对方向性强的纹理，在进行旋转变换后，可以提高纹理分类的正确率。
The result suggested that the correct classification ratio be increased by rotative transformation for the textures with intense direction.
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