Matching Interpolation of 3-D Images Based on Shape
Mao Xin-wei · Jisuanji fangzhen · 2005
In the case of image interpolation for 3D volume models, present methods either lack of the capability of interpolating gray levels and shapes at the same time, or need higher computation cost. In order to solve the problem, the paper introduces a shape-based 3D image matching interpolation algorithm. Firstly, the original images are segmented several regions with the threshold segmentation. Secondly, the contours of every region in the interpolated image are determined with the help of mathematical morphology. Finally, the values of interpolated points in the contour are obtained with the matching interpolation. Further, the whole image is obtained. The interpolated image overcomes not only the boundary blur of the different density matter, but also the shortcomings of the traditional shape-based interpolation algorithms. Compared with linear interpolation, the proposed algorithm greatly improves the quality of image. Moreover, the new algorithm has much lower computation cost compared with wavelet-based interpolation. The interpolation can be effectively used to construct 3D volume models.