Xinxin Ge, Haihua Cui, Zhenlong Xu, Minqi He, Xuezhi Han. Super-Resolution Image Reconstruction Method for Micro Defects of Metal Engine Blades[J]. Acta Optica Sinica, 2023, 43(2): 0210001
- Acta Optica Sinica
- Vol. 43, Issue 2, 0210001 (2023)
Fig. 1. Gray images of metal collected from multiple angles of light. (a) From the right; (b) from the bottom; (c) from the left; (d) from the top
Fig. 2. Schematic of photometric stereo hardware. (a) Hardware layout diagram; (b) light source vector calibration diagram
Fig. 3. Schematic for solving normal vector of highlighted points
Fig. 4. Surface normal map reconstructed by photometric stereo method
Fig. 5. Model network structure with super division ratio of 2
Fig. 6. In the process of upsampling on the network, the elements in the four feature layers correspond to the new feature layer graph
Fig. 7. Flow chart of proposed method
Fig. 8. Quantitative super-resolution reconstruction test platform. (a) Experiment platform; (b) shooting result
Fig. 9. Imaging detailed display of gray image. (e) Blade gray image; (b)-(e) corresponding local area pictures
Fig. 10. Gray scale images collected from different light source angles
Fig. 11. Detailed comparison of quantitative super-resolution reconstruction. (a) Blade normal map; (b)-(e) corresponding local area pictures
Fig. 12. Comparison of feature boundaries before and after fusion reconstruction. (a) Fig. 9 (b) area; (b) Fig. 11 (b) area
Fig. 13. Comparison of boundary extraction effects
Fig. 14. Comparison of high-resolution and low-resolution images in real images. (a) Original image; (b) local high-resolution image; (c) local down sampling low-resolution image
Fig. 15. Comparison of the effect of different super dividing networks on the surface image of metal blades. (a) Original picture; (b) local picture; (c)-(g) effects of local area using RDN,SRGAN,EDSR,SRCNN,and proposed method
Fig. 16. Metal blade image and surface defects. (a) Original picture; (b) local picture
Fig. 17. Strengthening results of different methods. (a) Method of Ref. [10]; (b) method of Ref. [5]; (c) proposed method
Fig. 18. Defect detection results by different methods. (a) Original detection image; (b) detection result by method of Ref. [10];
Fig. 19. Effect of micro defect boundary extraction after image super-resolution enhancement and reconstruction. (a) Local picture boundary extraction; (b) enhanced reconstruction feature extraction; (c)(d) detail enlarged view
|
Table 1. Comparison of the characteristics of several super-resolution networks
|
Table 2. Hyper parameters selection in the training process of super-resolution networks
| |||||||||||
Table 3. Test result confusion matrix
|
Table 4. Comparison of various super-resolution effects of metal blades
| |||||||||||||||||||||||||||||||||||||||
Table 5. Comparison of extraction effect of blade surface defects by different methods
Set citation alerts for the article
Please enter your email address
© Copyright 2018-2021 | Chinese Laser Press. All Rights Reserved 沪ICP备15018463号-20