Laser & Optoelectronics Progress, Volume. 59, Issue 14, 1415027(2022)
Performance Evaluation Method for Focusing Evaluation Operator in Superposed Large Depth Imaging
Focusing evaluation algorithms are the core of the superposed large depth of field imaging. Aiming at the experimental requirements of evaluating the performance of the focusing evaluation operator, we proposed a focusing evaluation operator performance evaluation method using image sequence sampling-point focusing evaluation and scatter plot Gaussian fitting. The performance evaluation experiments are performed on the existing focusing evaluation operators. Furthermore, we proposed a gradient-weighted image sharpness operator by modifying the traditional image sharpness index. The performance difference between the new and existing operators is compared using real and simulated images. The research results have certain reference significance for the implementation of stacking measurement.
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Chunshui Yu, Rongsheng Lu. Performance Evaluation Method for Focusing Evaluation Operator in Superposed Large Depth Imaging[J]. Laser & Optoelectronics Progress, 2022, 59(14): 1415027
Category: Machine Vision
Received: May. 25, 2021
Accepted: Jul. 28, 2021
Published Online: Jul. 1, 2022
The Author Email: Lu Rongsheng (rslu@hfut.edu.cn)