光学定向与测量技术研究室知识库

The traditional spatial domain sharpness evaluation functions usually have a larger amount of calculation, and the calculation time is relatively longer. Besides, its anti-noise ability is weak, and it is easy to be disturbed by the background factors in the image. The above problems will have an impact on the real-time, sensitivity and reliability of the auto-focus system. In order to overcome these shortcomings, an improved SML sharpness evaluation function combined with threshold is proposed in this paper. This algorithm improve the SML function firstly, and make full use of the edge information of the image. Then a threshold is introduced to distinguish the edge points from non-edge points. So it can not only highlight the edge information while restraining the noise and the flat area in the background of the image, but also can reduce the calculation amount of the evaluation function and improve the real-time performance of the auto-focusing system. Finally verifies the effect of the improved evaluation function based on the simulation experiments. The results show that the algorithm proposed in this paper has better sensitivity and anti-noise ability, and can evaluate the sharpness of defocused images accurately and steadily. © 2019 copyright SPIE. Downloading of the abstract is permitted for personal use only.