Multi-resolution MCS auto focus method in range-gated imaging system for underwater

被引:0
作者
You R. [1 ,2 ]
Wang X. [2 ]
Zhou Y. [2 ]
机构
[1] University of Chinese Academy of Sciences, Beijing
[2] Optoelectronic System Laboratory, Institute of Semiconductors, Chinese Academy of Sciences, Beijing
来源
| 2016年 / Chinese Society of Astronautics卷 / 45期
关键词
Auto focus; Experimental verification; Multi-resolution MCS; Range-gated imaging;
D O I
10.3788/IRLA201645.0726003
中图分类号
学科分类号
摘要
A real-time, accuracy and robustness multi-resolution mountain climb servo (MCS) auto focus method was proposed in order to solve real-time auto focus problem, and was obtained high clear high quality image because low clear low light images was difficult to realize auto focus in range-gated imaging system for underwater. The merits of this method were outstanding as follows. It reduced the amount of processing data and time by taking advantage of the image multi-resolution theory by spatial sampling of the current image and then formed different resolution sampling layers, which made the system possible to deal with auto focus more quickly as 1/2 time as traditional method. Thereby, the method calculated current frame weighted average edge detection image definition, which was determined by the correlation between current frame and two adjacent frames with 0.5, 0.3 and 0.2 coefficients before solving the error judge of interference maximum local peak. At last, the method realized the last operation auto focus by MCS. The repeated experimental verification of range-gated imaging system for underwater shows that the algorithms is capable of guaranteeing the auto focus speed and accuracy and improving the real-time, accuracy and robustness in focus determination. © 2016, Editorial Board of Journal of Infrared and Laser Engineering. All right reserved.
引用
收藏
页数:6
相关论文
共 9 条
  • [1] Tsagkatakis G., Woiselle A., Bousquet M., Et al., Multireturn compressed gated range imaging, Optical Engineering, 54, 3, (2015)
  • [2] Bulyshev A., Amzajerdian F., Roback V.E., Et al., Three-dimensional super-resolution: theory, modeling, and field test results, Applied Optics, 53, 12, pp. 2583-2594, (2014)
  • [3] Bianco G., Gallo A., Bruno F., Et al., A comparative analysis between active and passive techniques for underwater 3D reconstruction of close-range objects, Sensors, 13, 8, pp. 11007-11031, (2013)
  • [4] Cao Y., Wang X., Zhou Y., Spatical positioning fuzzy C-means algorithm in segmentation of range-gated image, Infrared and Laser Engineering, 42, 10, pp. 2862-2866, (2013)
  • [5] Azouz A.A.E., Li Z., Improved phase gradient autofocus algorithm based on segments of variable lengths and minimum-entropy phase correction, IET Radar, Sonar & Navigation, 9, 4, pp. 467-479, (2014)
  • [6] Mo C., Liu B., Ding L., Et al., A gradient threshold auto-focus algorithm, Infrared and Laser Engineering, 43, 1, pp. 323-327, (2014)
  • [7] Chiu H.L.C., Fuh C.S., An efficient auto focus method for digital still camera based on focus value curve prediction model, Journal of Information Science and Enginerring, 26, 4, pp. 1261-1272, (2010)
  • [8] Zhang Z., Wang Y., Xue G., Et al., Digital Image Processing and Computer Vision, pp. 100-102, (2014)
  • [9] Lu D., Wang X., Fan S., Et al., ns-scaled time-coding method for real-time 3D Super-resolution range-gated imaging, Chinese Optics Letters, 13, 8, pp. 1-5, (2015)