Lihua Yin, Juan Hang, Liang Kang, Shijian Liu. Infrared video image stabilization algorithm based on joint camera path[J]. Infrared and Laser Engineering, 2021, 50(6): 20200405
- Infrared and Laser Engineering
- Vol. 50, Issue 6, 20200405 (2021)
Fig. 1. Process of infrared video image stabilization algorithm based on joint camera path
Fig. 2. Motion model based on grid mapping. (a) Correspondence between two frames of image grids; (b) Shape retention constraints
Fig. 3. Schematic diagram of the joint camera path solution process. (a) Path iteration of the grid; (b) Relationship among the initial camera path C (t ), smooth path P (t ), and compensation path B (t )
Fig. 4. Comparison of image stability results in the case of abundant feature points and few feature points. (a) Rich feature point set；(b) Less feature point set
Fig. 5. Image corresponds to the joint camera path and the optimized path. (a) Corresponding grids between image frames; (b) Results before and after path optimization: the left side is the (1, 1) grid, and the right side is the (1, 1) grid
Fig. 6. Smoothing results before and after adding the second restraint. (a) Original image; (b) Without the second restraint; (c) Result in this paper
Fig. 7. Pseudo code of the algorithm in this paper
Fig. 8. Comparison of image stability results between single path and joint path. (a) Path optimization results; (b) Image after image stabilization: the left side is the single path, and the right side is the joint path
Fig. 9. Comparison of results of various image stabilization algorithms under the Driving type video. (a) Original image; (b) L1 algorithm; (c) AE system; (d) Zhu Juanjuan's electronic image stabilization algorithm; (e) Proposed algorithm
Fig. 10. Comparison of results of various image stabilization algorithms under the Zooming type video. (a) Original image; (b) L1 algorithm (c) AE system; (d) Zhu Juanjuan's electronic image stabilization algorithm; (e) Proposed algorithm
Fig. 11. Quantitative evaluation results of several image stabilization algorithms under seven sets of videos. (a) Simple; (b) Rotation; (c) Zooming; (d) Parallax; (e) Driving; (f) Crowd; (g) Running
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Table 1. Video image stabilization results under different grid cell sizes
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