Tian-yu ZHENG. Blurred star restoration based on improved Radon transform and sparse prior[J]. Optics and precision engineering, 2018, 26(6): 1470-1479.
DOI:
Tian-yu ZHENG. Blurred star restoration based on improved Radon transform and sparse prior[J]. Optics and precision engineering, 2018, 26(6): 1470-1479. DOI: 10.3788/OPE.20182606.1470.
Blurred star restoration based on improved Radon transform and sparse prior
A New blurred star spot restoration algorithm was proposed to improve the accuracy of the centroiding of star of the star navigation system under dynamic conditions in this paper. Firstly
the star blurring model was analyzed
and the conclusion that the accuracy of the centroiding of the star increased with the signal to noise ratio(SNR) was obtained. The recovery of the blurred star was divided into coarse and fine steps for the carrier angular motion and vibration. The effect of noise on Radon transform was analyzed
and an improved Radon transform algorithm for gray stretching was proposed. Finally
the iterative blind restoration algorithm was used to perform the precise restoration of star spot based on the sparse prior regularization of the gradient distribution of the clear star spot. The simulation and experimental results show that the peak signal to noise ratio (PSNR) of the two step blurred star spot restoration algorithm is improved by 30% and the precision of centroid positioning is improved by 55%
compared with the traditional algorithm.
关键词
Keywords
references
KAZEMI L, ENRIGHT J, DZAMBA T. Improving star tracker centroiding performance in dynamic imaging conditions[C]. Aerospace Conference , 2015 IEEE. IEEE , 2015: 1-8. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7119226
MA L, WANG X, ZHAN D, et al. . Extraction method of the motion blurred star image for the star sensor under high dynamic conditions[C]. Signal Processing ( ICSP ), 2014 12 th International Conference on. IEEE , 2014: 836-840. http://ieeexplore.ieee.org/document/7015121/
QIAN X, YU H, CHEN S. A Global-shutter centroiding measurement CMOS image sensor with star region SNR improvement for star trackers[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2016, 26(8):1555-1562.
YAN J, JIANG J, ZHANG G. Dynamic imaging model and parameter optimization for a star tracker[J]. Optics Express, 2016, 24(6):5961-5983.
SUN T, XING F, YOU Z, et al.. Motion-blurred star acquisition method of the star tracker under high dynamic conditions[J]. Optics Express, 2013, 21(17):20096-20110.
HOU W, LIU H, LEI Z, et al.. Smeared star spot location estimation using directional integral method[J]. Applied optics, 2014, 53(10):2073-2086.
SUN T, XING F, YOU Z, et al.. Smearing model and restoration of star image under conditions of variable angular velocity and long exposure time[J]. Optics express, 2014, 22(5):6009-6024.
SU L, SHAO X, WANG L, et al . . Richardson-Lucy deblurring for the star scene under a thinning motion path[C]. SPIE Sensing Technology Applications. International Society for Optics and Photonics , 2015: 95010L-95010L-9. http://spie.org/Publications/Proceedings/Paper/10.1117/12.2176782
WANG K, ZHANG C, LI Y, et al.. A new restoration algorithm for the smeared image of a SINS-aided star sensor[J]. The Journal of Navigation, 2014, 67(5):881-898.
SUN H, DESVIGNES M, YAN Y, et al . . Motion blur parameters identification from radon transform image gradients[C]. Industrial Electronics , 2009. IECON '09. 35 th Annual Conference of IEEE. IEEE , 2009: 2098-2103. http://ieeexplore.ieee.org/xpls/icp.jsp?arnumber=5415110
WEI Q, WEINA Z. Restoration of motion-blurred star image based on Wiener filter[C]. Intelligent Computation Technology and Automation ( ICICTA ), 2011 International Conference on. IEEE , 2011, 2: 691-694. http://doi.ieeecomputersociety.org/10.1109/ICICTA.2011.458
XIAO J W, XIN L W. Multiple blur of star image and the restoration under dynamic conditions[J]. Acta Astronautica, 2011, 68(11):1903-1913.
FAHMY M F, RAHEEM G M A, Mohamed U S, et al.. A new fast iterative blind deconvolution algorithm[J]. Journal of Signal and Information Processing, 2012, 3(01):98.
XU L, ZHENG S, JIA J. Unnatural l0 sparse representation for natural image deblurring[C]. Proceedings of the IEEE conference on computer vision and pattern recognition , 2013: 1107-1114. http://doi.ieeecomputersociety.org/10.1109/CVPR.2013.147