A New Auto-Extraction Algorithm of Lunar Craters for Chang’E Data Based on the Solar Incidence Angle

Abstract:

A new algorithm for detecting lunar craters based on the solar incidence angle has been proposed, which converts the Chang’E CCD images to binary images first by detecting edges in the Chang’E CCD images, then the new algorithm calculates the average angle of the solar incidence angles of each edge, Comparing the average angle of each edge with the solar incidence angle of the whole image to delete those noise/false edges of craters. Finally, the common circle fitting has been implemented to detect craters from those edge images. The new algorithm proposed has been tested on different Mare areas and all testing results had shown that the new algorithm could get a satisfying effect.

• Periodical: Applied Mechanics and Materials (Volumes 599-601)
• Pages: 1333-1339
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.599-601.1333
• Online since: August 2014
• Authors: Zi Hao Ren*, Hong Kun Jiang, Wen Liang Du, Xiao Lin Tian, Ao Ao Xu
• Keywords: Chang’E Data, Crater Identification, Solar Incidence Angle

References

[1] Liu Y X, Liu J J, Mu L L, et al. A review of impact-crater detection (in Chinese). Astron Res Tech, 2012, 9(2): 203–212.

[2] Wan C, Cheng W M, Zhou Z P, et al. Automatic extraction of lunar impact craters from Chang'E-1 satellite photographs. Sci China-Phys, Mech Astron, 2012, 55: 162–169.

DOI: 10.1007/s11433-011-4584-6

[3] Kim J R, Muller JP, van Gasselt S, et al. Automated crater detection, a new tool for mars cartography and chronology[J]. Photogrammetric Engineering and Remote Sensing, 2005, 71(10): 1205-1217.

DOI: 10.14358/pers.71.10.1205

[4] Bandeira L P C, Saraiva J, Pina P. Development of a methodology for automated crater detection on the planetary image[M]/ Pattern Recognition and Image Analysis. Berlin: Springer, 2007: 193-200.

DOI: 10.1007/978-3-540-72847-4_26

[5] Feng JunHua, Cui HuTao, Cui PingYuan, Tian Yang, Planetary surface crater monitoring and matching methods has been propesed in ACTA AERONAUTICA ET ASTRONAUTICASINICA, (2010).

DOI: 10.1109/isscaa.2010.5633604

[6] Cheng Y, Miller J K, Autonomous landmark based spacecraft navigation system[C]/2003 AAS/AIAA Astrodynamics Specialist Conference. Ponce, Puerto Rico: (2003).

[7] Cheng Y, Miller J K, Matthies L H, et al. Optical landmark detection for spacecraft navigation[C]/13th Annual AAS/AIAA Space Flight Mechanics Meeting. Ponce, Puerto Rico: (2003).

[8] John Canny. A Computational Approach to Edge Detection [J]. IEEE Trans. Pattern Analysis and Machine Intelligence (S0162-8828) , 1986 , 8(6)：679-6981999.

DOI: 10.1109/tpami.1986.4767851

[9] Wei Yi, Xu HuaZhong, An ellopse identify fast algorithm based on the theory of error. Information science and electronic engineering. 2005, 12, third volume, No 4.

[10] JIANG HongKun, TIAN XiaoLin, XU AoAo, An automatic algorithm for detecting lunar impact craters which has been proposed in a defined feature space, SCIENTIA SINICA Physica, Mechanica & Astronomica, 2013, 43(11): 1430-1437.

DOI: 10.1360/132013-321