Sequence Image Registration for Large Depth of Microscopic Focus Stacking

Ang Wu,Rongsheng Lu,Yanqiong Shi,Zilong Zhang

doi:10.1109/access.2019.2963633

Abstract

The large depth of images for microscopic measurement can be achieved by using focus stacking techniques with a small depth of field of objective lens. It is implemented by fusing the image sequences of short depth images. However, the non-linear movement of the objective imaging system or the measured object caused by the moving stage straightness error brings the misalignment of the image sequences, such as transversal translation, rotation, and tilting. All of these interferences, as well as the image brightness variation must be corrected by image registration before fusing the image sequences. In this paper, a fast-automatic registration method based on the scale invariant feature transform (SIFT) is proposed. It is achieved by firstly segmenting the focal regions of the image sequences through fast edge detection. Then the image features are extracted within the small segmented focal areas. It greatly reduces the computational cost of feature extraction and the following steps of image correction, and alignment. In the process, the random sampling consistency (RANSAC) algorithm is also used to remove the mistake features. The Laplacian pyramid method is adopted for the large depth of image fusion. The experimental results show that the proposed method is more efficient than the traditional SIFT algorithm. Its registration efficiency is improved by about 60%. This method facilitates the high-precision and real-time imaging of a monocular three-dimensional focus stacking.

Highlights

Focus/defocus imaging technology [1] has been widely used in the field of three-dimensional (3D) microscopic measurement, such as 3D measurement with the focus variation method [2], 3D imaging through focus stacking [3], and extending depth of field from different focused images [4]
A fast-automatic and high-precision registration method based on scale invariant feature transform (SIFT) was proposed
The image registration method based on self-adaptive and fast segmentation of the focus area improves dramatically the registration speed under the premise of ensuring the registration accuracy

Summary

INTRODUCTION

Focus/defocus imaging technology [1] has been widely used in the field of three-dimensional (3D) microscopic measurement, such as 3D measurement with the focus variation method [2], 3D imaging through focus stacking [3], and extending depth of field from different focused images [4]. SIFT algorithm has high detection accuracy and robustness in image scale transformation, rotation, scaling, and illumination change It has the disadvantages of high computational complexity and timeconsuming, which makes it difficult to meet the requirements of real-time detection. To meet the requirement of real-time and high accuracy in engineering for monocular 3D focus stacking microscopic measurement, the key problem is to improve the registration speed and accuracy. On the other hand, according to the characteristics of the microscopic imaging of focus stacking, when the measured object is in the out-of-focus position, the pixel position of the object is imaged with a certain offset, and the registration based on focal areas has a certain feasibility in improving the registration accuracy.

RELATED WORK

THE PROPOSED METHOD

FEATURE DETECTION IN SCALE SPACE

CONCLUSION