Spinal Sequence Automatic Stitching Based on Biorthogonal Wavelet Transform and Feature Matching
10.3969/j.issn.1005-202X.2010.02.007
- VernacularTitle:基于双正交小波变换与特征匹配的脊柱序列自动拼接
- Author:
Xue MENG
;
Zhensheng DENG
;
Xin GUO
- Publication Type:Journal Article
- Keywords:
spinal X-ray image sequence;
biorthogonal wavelet transform;
feature matching;
RANSAC;
automatic stitching
- From:Chinese Journal of Medical Physics
2010;27(2):1726-1730
- CountryChina
- Language:Chinese
-
Abstract:
Objective: An automatic seamless stitching method with spinal X-ray image sequence is presented in this paper. Methods: First, biorthogonal wavelet transform is used to implement decomposing of the multi-resolution and the effective edge of the image can be extracted by this method combined with Canny operator. The feature points of the image can be obtained by calculating the edge contour matrix E and the value matrix H. Second, the roughly matching of feature points can be achieved by using Normalized Cross Correlation (NCC) algorithm and the random sample consensus (RANSAC) algorithm is introduced to remove false matching pairs and to achieve precisely matching. Third, the image sequence is automatically sorted with the improved genetic algorithm to achieve automatic stitching. At last, the weighted average fusion algorithm is appfied to achieve smooth and seamless image stitching. This algorithm is robust for the weak-contrast X-ray image sequence. Results: Experimental results show that high-quality and fast image sequence stitching can be obtained automatically by using this method. Conclusions: To a certain extent, it overcomes the shortcomings of X-ray image sequence such as the strong image noise, concentration of values ofpixels, blurred boundaries, large overlap area and the sequence constraint, and therefore it may be applied to in medical imaging field widely.
