Research on large-field microscopic images based on the best stitching path

doi:10.3969/j.issn.1000-5641.2021.06.009

Abstract

Abstract:

Image stitching technology is one of the key technologies in the application of large-field microscopic digital images. The existing traditional image stitching method is to stitch in a fixed order after image registration, and once there is an error, it will be accumulated along a fixed path, thereby causing problems such as misalignment of subsequent images. In this study, through experimental analysis, a method for optimizing the stitching path of the large-field image was proposed, which greatly optimized the problems caused by error accumulation and registration failure, and effectively improved the stitching quality of the large-field microscopic digital image. This method can be used not only for the stitching of large-field microscopic images, but also for other types of stitching.

Key words: large-field microscopic digital image, error accumulation, image registration, optimal stitching path

CLC Number:

TP751

Yang XU, Hongying LIU, Quanjie ZHUANG. Research on large-field microscopic images based on the best stitching path[J]. Journal of East China Normal University(Natural Science), 2021, 2021(6): 81-87.

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配准方法	匹配对数量/对			耗时/s
配准方法	暴力匹配后	阈值过滤后	随机抽样一致性后	耗时/s
SIFT	350	15	13	1.142
SURF	144	12	11	0.763
GPU版本SURF	105	2	2	0.007

拼接方法	路径上配准失败数/个	路径上配准对总数/对	失误率/%
传统拼接	58	611	9.5
T = T_Cu方法	39	611	6.4
T = T_Cu × T_Ad方法	32	611	5.2