The precise stitching of microscopic images of large-scale biological sequence slices is of great significance for the study of biological structure and function, but the slight scale changes of microscopic images and the blank areas in the images seriously affect the accuracy of mosaic. In this paper, we propose a electron microscope sequence image stitching based on belief propagation algorithm, which basically solves this problem. Firstly, the relative scale of adjacent images is calculated by extracting the sift feature points of the images. Then the global optimization model is used to obtain the absolute scale of each image, and the image is scaled to obtain the microscopic image with consistent scale. Secondly, obtain the relative displacement relationship of adjacent images by template matching method, and then the global positions of all images are optimized by Belief Propagation (BP) algorithm to eliminate the influence of blank regions and repetitive structures on the stitching results. In the case study, the proposed method demonstrates high quality.
Registration of electron microscopy (EM) images is one of the most important steps in reconstructing neurons. Image registration algorithm based on SIFT have been widely used in the EM image registration. But SIFT matching procedure both costs a lot of time and introduce massive false matches. In this paper, we propose an improved EM image registration method using the scale information of SIFT keypoints. In the feature matching procedure, our method saves up to 45.8% of the computation time compared to SIFT. We also added a preprocessing procedure for RANSAC to eliminate false matches in small-scale matches sets. Experimental results show that the method improves the accuracy of results on every test EM image set while highly reducing the registration time.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.