A fast algorithm for material image sequential stitching
A fast algorithm for material image sequential stitching
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DOI：
10.1016/j.commatsci.2018.10.044
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发表时间：
2019-02
影响因子：
3.3
通讯作者：
Boyuan Ma;X. Ban;Haiyou Huang;Wanbo Liu;Chuni Liu;Di Wu;Yonghong Zhi
中科院分区：
文献类型：
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作者：
Boyuan Ma;X. Ban;Haiyou Huang;Wanbo Liu;Chuni Liu;Di Wu;Yonghong Zhi
在材料研究中，通常非常希望观察具有高分辨率的整个显微切片的图像。因此，显微图像拼接是一种重要的技术，通过将具有重叠区域的多幅图像组合在一起来产生全景或更大的图像，同时保持微观分辨率。然而，由于高复杂性和多样性的微观结构，大多数传统的方法不能平衡的速度和准确性的拼接策略。为了克服这个问题，我们提出了一种快速的连续显微图像拼接方法（VFSMS），该方法采用增量搜索策略和GPU加速来保证拼接结果的准确性和速度。实验结果表明，VFSMS在三种类型的微观数据集上的准确性和速度方面都达到了最先进的性能。此外，它明显优于最著名和最常用的软件，如ImageJ，Photoshop和Autostitch。该软件可在https://www.mgedata.cn/app_entrance/microscope上获得。
In material research, it is often highly desirable to observe images of whole microscopic sections with high resolution. So that micrograph stitching is an important technology to produce a panorama or larger image by combining multiple images with overlapping areas, while retaining microscopic resolution. However, due to high complexity and variety of microstructure, most traditional methods could not balance speed and accuracy of stitching strategy. To overcome this problem, we develop a method named very fast sequential micrograph stitching (VFSMS), which employ incremental searching strategy and GPU acceleration to guarantee the accuracy and the speed of stitching results. Experimental results demonstrate that the VFSMS achieve state-of-art performance on three types’ microscopic datasets on both accuracy and speed aspects. Besides, it significantly outperforms the most famous and commonly used software, such as ImageJ, Photoshop and Autostitch. The software is available at https://www.mgedata.cn/app_entrance/microscope.