Auto-focus algorithm based on improved SML evaluation function | |
Ma, Xiaoyu1,2; Li, Qiaoling2 | |
2019 | |
会议日期 | 2019-07-07 |
会议地点 | Beijing, China |
关键词 | auto-focus sharpness evaluation function threshold gradient SML image processing |
卷号 | 11338 |
DOI | 10.1117/12.2545624 |
英文摘要 | The traditional spatial domain sharpness evaluation functions usually have a larger amount of calculation, and the calculation time is relatively longer. Besides, its anti-noise ability is weak, and it is easy to be disturbed by the background factors in the image. The above problems will have an impact on the real-time, sensitivity and reliability of the auto-focus system. In order to overcome these shortcomings, an improved SML sharpness evaluation function combined with threshold is proposed in this paper. This algorithm improve the SML function firstly, and make full use of the edge information of the image. Then a threshold is introduced to distinguish the edge points from non-edge points. So it can not only highlight the edge information while restraining the noise and the flat area in the background of the image, but also can reduce the calculation amount of the evaluation function and improve the real-time performance of the auto-focusing system. Finally verifies the effect of the improved evaluation function based on the simulation experiments. The results show that the algorithm proposed in this paper has better sensitivity and anti-noise ability, and can evaluate the sharpness of defocused images accurately and steadily. © 2019 copyright SPIE. Downloading of the abstract is permitted for personal use only. |
产权排序 | 1 |
会议录 | AOPC 2019: Optical Sensing and Imaging Technology |
会议录出版者 | SPIE |
语种 | 英语 |
ISSN号 | 0277786X;1996756X |
ISBN号 | 9781510634480 |
WOS记录号 | WOS:000525830600068 |
内容类型 | 会议论文 |
源URL | [http://ir.opt.ac.cn/handle/181661/93211] |
专题 | 西安光学精密机械研究所_光学定向与测量技术研究室 |
作者单位 | 1.University of Chinese, Academy of Sciences, Beijing; 100049, China 2.Xi'an Institute of Optics and Precision Mechanics of CAS, Xi'an; 710119, China; |
推荐引用方式 GB/T 7714 | Ma, Xiaoyu,Li, Qiaoling. Auto-focus algorithm based on improved SML evaluation function[C]. 见:. Beijing, China. 2019-07-07. |
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