中国医疗设备2024，Vol.39Issue(5)：1-8,47,9.DOI:10.3969/j.issn.1674-1633.2024.05.001
基于分类配准与全景像素坐标系的显微图像快速拼接算法
Fast Stitching Algorithm of Microscopic Images Based on Classification Registration and Panoramic Pixel Coordinate System
摘要
Abstract
Objective Based on classification registration and panoramic pixel coordinate system,to propose a real-time microscopic image mosaic algorithm to solve the problems of low accuracy and high computational complexity of existing image mosaic algorithms.Methods According to the quality characteristics of the single field image,the evaluation function was utilized to classify and align the images to adapt to different alignment models.A panoramic pixel coordinate system was constructed,and overall splicing and seam fusion were carried out under this coordinate system according to the alignment results.Experiments were carried out based on the self-built urine sample micro-scanning system to verify the effectiveness of the algorithm.Results The experimental results showed that compared with the existing image mosaic methods,the rapid microscopic image mosaic algorithm based on classification registration and panoramic pixel coordinate system was more conducive to the fusion of stitching gaps,and was more stable,and the stitching effect was significantly better than that of speeded up robust features and fast Fourier transform alone.In terms of stitching time,the real-time stitching algorithm of microscopic images based on classification registration and panoramic pixel coordinate system greatly reduced the splicing time,and the splicing speed was doubled.Moreover,for large-field images stitched in rectangular scanning area,there was no obvious stitching gap trace,and high-quality real-time stitching can be completed.Conclusion The rapid microscopic image mosaic algorithm based on classification registration and panoramic pixel coordinate system can meet the needs of fast and high-resolution large-field image stitching,and can provide a more favorable method for the microscopic image mosaic method,facilitating the further analysis by the related personnel.关键词
显微图像/特征点检测/图像拼接/快速傅里叶变换Key words
speeded up robust features/feature point detection/image mosaic/fast Fourier transform分类
医药卫生引用本文复制引用
刘伟强,吴杰,王红强,朱华庆..基于分类配准与全景像素坐标系的显微图像快速拼接算法[J].中国医疗设备,2024,39(5):1-8,47,9.基金项目
国家自然科学基金(61973295) （61973295）
安徽省重点研发项目(201904a07020092). （201904a07020092）
