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Structural medical image fusion by means of dual tree complex wavelet

机译:利用双树复小波进行结构医学图像融合

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This paper presents a new method for fusion of medical images. It has been shown that 2-D wavelets are not sufficient for decomposition of images due to lack of directionality and shift variance. Complex wavelet transforms stand as a candidate to overcome deficiencies of wavelet transform. This paper exploits dual tree complex wavelet transform to decompose image and fuse the details and approximations based on maxima and averaging fusion rules. Results of visual and quantitive analysis prove efficiency of the method over conventional multiresolution methods in terms of mutual information, entropy and standard deviation.
机译:本文提出了一种融合医学图像的新方法。已经表明,由于缺乏方向性和移位方差,二维小波不足以分解图像。复杂小波变换可以克服小波变换的不足。本文利用对偶树复小波变换对图像进行分解,并基于极大值和平均融合规则对细节和近似进行融合。视觉和定量分析的结果证明了该方法在互信息,熵和标准差方面优于传统的多分辨率方法。

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