Research of Image Sharpness Assessment Algorithm for Autofocus
文献类型：会议论文
| 作者 | Her, Lilin1,2; Yang, Xiaojun1
|
| 出版日期 | 2019-07 |
| 会议日期 | 2019-07-05 |
| 会议地点 | Xiamen, China |
| 关键词 | sharpness evaluation function autofocus gradient operator brenner algorithm |
| DOI | 10.1109/ICIVC47709.2019.8980980 |
| 页码 | 93-98 |
| 英文摘要 | With the wide application of imaging system in security monitoring, aerospace, medical image and other fields, how to capture the clear image of the target in real time and automatically is particularly important. Image sharpness evaluation function is the key to evaluate the imaging quality of various imaging systems. The spatial gradient evaluation algorithm is based on the direct processing of image pixels, and the calculation is simple and intuitive. In this paper, we compare the performance of image sharpness evaluation functions in four spatial domains through two sets of atlases with different background richness. Experiments show that Benner algorithm has high scene adaptability and strong anti-jamming ability; Laplace algorithm has high sensitivity and can get results quickly in different size images; Tenengrad algorithm can reduce the occurrence of local extremum after selecting a certain threshold; Robert algorithm has poor unimodality and accuracy in two sets of atlas test. © 2019 IEEE. |
| 产权排序 | 1 |
| 会议录 | 2019 IEEE 4th International Conference on Image, Vision and Computing, ICIVC 2019
 |
| 会议录出版者 | Institute of Electrical and Electronics Engineers Inc. |
| 语种 | 英语 |
| ISBN号 | 9781728123257 |
| 源URL | [http://ir.opt.ac.cn/handle/181661/93433]  |
| 专题 | 西安光学精密机械研究所_光电测量技术实验室 |
| 作者单位 | 1.Chinese Academy of Sciences, Xi'An Institute of Optics and Precision Mechanics, Xi'an, China; 2.University of Chinese Academy of Sciences, Beijing, China |
| 推荐引用方式 GB/T 7714 | Her, Lilin,Yang, Xiaojun. Research of Image Sharpness Assessment Algorithm for Autofocus[C]. 见:. Xiamen, China. 2019-07-05. |
入库方式： OAI收割
来源：西安光学精密机械研究所
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