摘要:
现有插值方法在进行医学断层图像插值时,不能兼顾灰度和形状的变化.为解决这一
问题,文中提出一种基于小波的医学图像插值算法.通过对原图进行小波变换,获得图像边缘对
应小波系数的位置信息,在断层图像的相应小波系数之间进行强度和位置插值,使新的图像不
仅在灰度上,而且在组织形状上,介于原来的断层图像之间,满足了医学图像插值的要求.与线
性插值、克立格插值相比,新算法的视觉效果好,计算误差小,插值结果可有效地应用于构建三
维体模型.
Abstract:
In the case of medical image interpolation for 3D volume models, present
methods lack the capability of interpolating gray levels and shapes at the same time. In
order to solve the problem, the paper introduces a wavelet-based medical image interpolation
algorithm. Firstly, the algorithm decomposes the original images with
wavelet analysis and obtains the positions of wavelet coefficients that belong to the
edges. Then, the algorithm interpolates intensities and positions of those wavelet coefficients
between corresponding wavelet sub-images. So that the new image basically
satisfies the requirements of medical image interpolation. Compared with linear interpolation
and Kriging interpolation, the new algorithm has a good visual effect and the
squared error is small. The interpolation can be effectively used to construct 3D-volume models.
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