Laser-induced damage tests based on a marker-based watershed algorithm with gray control
1 Joint Laboratory on High Power Laser and Physics, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai 201800, PR China
2 University of Chinese Academy of Sciences, Beijing 100039, PR China
Figures & Tables
Fig. 1. Flow chart of the imaging process using the MWGC.
下载图片 查看原文
Fig. 2. Results of image segmentation. (a) Original damage image; (b) by image binarization; (c) by threshold segmentation; (d) by marker-based watershed algorithm without gray control; (e) by MWGC.
下载图片 查看原文
Fig. 3. Damage site morphology captured by OM.
下载图片 查看原文
Fig. 4. Experimental set-up for laser-induced damage testing.
下载图片 查看原文
Fig. 5. Temporal profile of a 3 ns pulse at 1053 nm.
下载图片 查看原文
Fig. 6. (a) Near-field energy density distribution at 351 nm. (b) Profile along the line in (a).
下载图片 查看原文
Fig. 7. Damage growth of (a) Corning-7980 and (b) Heraeus-Suprasil 312 samples at 351 nm.
下载图片 查看原文
Fig. 8. Damage site size distribution for the Corning-7980 sample at 351 nm.
下载图片 查看原文
Fig. 9. Damage site size distribution for the Heraeus-Suprasil 312 sample at 351 nm.
下载图片 查看原文
Table2. Pixel Size Calibration for Different Damage Images.
| No. | Corresponding sample | Pixel size ($\mu $m/pixel) |
|---|
| 1 | Corning-7980 | 7.09 | | 2 | Heraeus-Suprasil 312 | 7.32 |
|
查看原文
Table3. Damage growth for Corning-7980 and Heraeus-Suprasil 312 samples.
| Sample | Average | Average | Standard | Fitting |
|---|
| fluence | growth | deviation of | goodness |
|---|
| (J cm ) | coefficient | growth coefficient |  (%) |
|---|
| Corning-7980 | 9.60 | 1.10 | 0.31 | 98.8 | | Heraeus-Suprasil 312 | 8.56 | 0.60 | 0.09 | 97.3 |
|
查看原文
Yajing Guo, Shunxing Tang, Xiuqing Jiang, Yujie Peng, Baoqiang Zhu, Zunqi Lin. Laser-induced damage tests based on a marker-based watershed algorithm with gray control[J]. Collection Of theses on high power laser and plasma physics, 2014, 12(1): e21.
m)
m)
m)
3.0
3.0
7.2
2.1
1.0
8.8
m)
PDF全文
