Name
Abstract | ||
|---|---|---|
When the pulse-sequence-based image sensor films high-speed moving objects, the image lag problem may appears as blurring in reconstructed images. In this paper, an algorithm is proposed to suppress lags by distinguishing the lag area and calculating ratio of bright to dark part in one trigger interval. The algorithm bases on the sensors characteristics and image lag principle that the change of light intensity cannot be immediately reflected on the pulse generated from photoelectric accumulation. The effectiveness of the algorithm is verified both on the sensors behavior-level model and the real image sensor. In both experiments the curves of LSF (line spread function) and MTF (modulation transfer function) show the reconstructed edges after lag elimination algorithm are similar to the real edges both in sharpness and position. The indexes to evaluate image similarity including LMD (location mean deviation), PSNR (peak signal to noise ratio) and SSIM (structural similarity index) improve respectively. In the experiment on sensors model, when the simulation velocity of edge is low, the algorithm can reconstruct the perfect edges as input images. As velocity increases, the reconstructed edges are still sharp but with slight shifts. In the real experiment to film a turntable with a rotation speed of 6000r/min, the LMD, PSNR and SSIM improve from 22.2833 to 2.5167, 18.2485 to 21.8603 and 0.8345 to 0.9364 respectively. These results show that the algorithm can suppress image lag and improve reconstructed image quality. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/ACCESS.2019.2948110 | IEEE ACCESS |
Keywords | DocType | Volume |
Image reconstruction, Image sensors, Image edge detection, Threshold voltage, Films, Image segmentation, Indexes, High-speed, pulse-sequence-based image sensor, image reconstruction, lag elimination, algorithm | Journal | 7 |
ISSN | Citations | PageRank |
2169-3536 | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jiangtao Xu | 1 | 31 | 12.56 |
| Peiwen Zhang | 2 | 0 | 0.68 |
| Zhe Yang | 3 | 0 | 0.34 |
| Zhiyuan Gao | 4 | 17 | 9.39 |
| Kaiming Nie | 5 | 35 | 8.77 |
| Jianguo Ma | 6 | 13 | 2.52 |