最后对待配准图像进行刚体变换及双线性插值，从而实现图像配准。
Finally, the rigid transformation and bilinear interpolation in the image prepared for registration is carried out to realize image registration.
本文提出的算法适应性较强，在重复性纹理、旋转角度比较大等较难自动匹配场合下仍可以准确实现图像配准。
In this paper, the algorithm adapted, in the repetitive texture, such as relatively large rotation more difficult to automatically match occasions can still achieve an accurate image registration.
针对模糊图像的弱点，分析了通过增强象素模糊属性对比度来提取边界特征的基本原理，实现了两幅图像的配准。
Aiming at the disadvantage of fuzzy image, by making some analysis about extracting edge feature based on fuzzy contrast enhancement algorithm, two images registration is achieved.
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