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New structure for multi-aspect SAR image target recognition with multi-level joint consideration

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Abstract

A new structure for SAR target recognition using multi-aspect SAR images is proposed. The new structure applies new approaches in the two levels of SAR image target recognition, which are data level and decision level, and combines the benefits of the two. Projections onto convex sets (POCS) super-resolution reconstruction algorithm is used in the data level of the new structure, which is to advance the resolution of the SAR image by using a series of multi-aspect SAR images. Weighted Bayes decision fusion algorithm is proposed in the decision level to jointly consider the benefit from the data level. All outcomes from the classifiers are fused in the decision level to generate the final result, which combines the multi-level benefits. Verification and analysis is performed to the proposed structure with multi-target image data in MSTAR database. Experimental results indicate that using the proposed structure for multi-aspect SAR images with multi-level joint consideration, the recognition rate is significantly advanced than that using single SAR target image. Meanwhile, the recognition rate by this structure is also higher than that using individual level approach.

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References

  1. Bhanu B, Jones G (2002) Exploiting azimuthal variance of scatters for multiple look SAR recognition. Proc SPIE 4727:290–298. doi:10.1117/12.478686

    Article  Google Scholar 

  2. Brendel G, Horowitz L (2000) Benefits of aspect diversity for SAR ATR: fundamental and experimental results. Proc SPIE 4053:567–578. doi:10.1117/12.396367

    Article  Google Scholar 

  3. Brown MZ (2003) Analysis of multiple-view Bayesian classification for SAR ATR. Proc SPIE 5095:265–274. doi:10.1117/12.487171

    Article  Google Scholar 

  4. Ettinger G, Snyder W (2002) Model-based fusion of multi-look SAR for ATR. Proc SPIE 4727:277–289. doi:10.1117/12.478685

    Article  Google Scholar 

  5. Fung Y, Chan Y (2006) A POCS-based restoration algorithm for restoring halftoned color-quantized images. IEEE Trans Image Process 15(7):1985–1992. doi:10.1109/TIP.2006.873432

    Article  MathSciNet  Google Scholar 

  6. He C, Liu L, Liu M, Feng Q, Liao M (2011) SAR super resolution via multi-dictionary. Proc. 2011 I.E. International Geoscience and Remote Sensing Symposium, Vancouver, Canada, 366–369

  7. Hong Y, Ma X, Huang H, Qi C (2008) Face image super-resolution through POCS and residue compensation. Proc. 5th International Conference on Visual Information Engineering, Xi’an, China, 494–497. doi:10.1049/cp:20080364

  8. Hsu JT, Yen CC, Li CC, Sun M, Tian B, Kaygusuz M (2004) Application of wavelet-based POCS super-resolution for cardiovascular MRI image enhancement. Proc. the Third International Conference on Image and Graphics, Hong Kong, China, 572–575

  9. Huan R, Mao K, Lei Y, Yu J, Xia M (2010) SAR Target Recognition with Data Fusion. Proc. 2010 WASE International Conference on Information Engineering, Beidaihe, Hebei, China, 2:19–23. doi:10.1109/ICIE.2010.101

  10. Huan R, Pan Y (2013) Target recognition for multi-aspect SAR images with fusion strategies. Prog Electromagn Res 134:267–288. doi:10.2528/PIER 12100304

    Article  Google Scholar 

  11. Ito Y (2009) Resolution enhancement of SAR image using a multiframe super resolution technique. Proc 2009 I.E. International Geoscience and Remote Sensing Symposium, Cape Town, South Africa, IV-446–IV449. doi:10.1109/IGARSS.2009.5417409

  12. Novak LM, Owirka GJ, Brower WS (1998) An efficient multi-target SAR ATR algorithm. Proc. the Thirty-Second Asilomar Conference on Signals, Systems & Computers, Pacific Grove, CA, USA, 1:3–13. doi:10.1109/ACSSC.1998.750815

  13. Novak LM, Owirka GJ, Brower WS (2000) Performance of 10- and 20-Target MSE classifiers. IEEE Trans Aerosp Electron Syst 36:1279–1289

    Article  Google Scholar 

  14. O’Sullivan JA, DeVore MD, Kedia V, Miller MI (2001) SAR ATR performance using a conditionally Gaussian model. IEEE Trans Aerosp Electron Sys 37(1):91–108. doi:10.1109/7.913670

    Article  Google Scholar 

  15. Ross T, Worrell S, Velten V, Mossing J, Bryant M (1998) Standard SAR ATR evaluation experiments using the MSTAR public release data set. Proc SPIE 3370:566–573. doi:10.1117/12.321859

    Article  Google Scholar 

  16. Sandirasegaram N, Englisth R (2005) Comparative analysis of feature extraction (2D FFT and wavelet) and classification (Lp metric distances, MLP NN, and HNeT) algorithms for SAR imagery. Proc SPIE 5808:314–325. doi:10.1117/12.597305

    Article  Google Scholar 

  17. Sezan MI, Stark H (1982) Image restoration by the method of convex projections: part 2-applications and numerical results. IEEE Trans Med Imaging MI-1(2):95–101. doi:10.1109/TMI.1982.4307556

    Article  Google Scholar 

  18. Snyder W, Ettinger G (2003) Performance models for hypothesis-level fusion of multi-look SAR ATR. Proc SPIE 5095:396–407. doi:10.1117/12.487036

    Article  Google Scholar 

  19. Stark H (1990) Convex projections in image processing. IEEE Trans Image Process 2034–2036. doi:10.1109/ISCAS.1990.112153

  20. Stark H, Oskoui P (1989) High-resolution image recovery from image-plane arrays using convex projections. J Opt Soc Am 6(11):1715–1726. doi:10.1364/JOSAA.6.001715

    Article  Google Scholar 

  21. Su H, Zhang X, Wei S (2010) Resolution enhancement of SAR image using the modified IBP method. Proc. 2010 2nd International Conference on Signal Processing Systems, Dalian, China, V2-486–V2-489. doi:10.1109/ICSPS.2010.5555838

  22. Sundareshan MK, Bhattacharjee S (2004) Enhanced iterative processing algorithms for restoration and superresolution of tactical sensor imagery. Opt Eng 43(1):199–208. doi:10.1117/1.1626665

    Article  Google Scholar 

  23. Vapnik VN (1999) An overview of statistical learning theory. IEEE Trans Neural Netw 10(5):988–999. doi:10.1109/72.788640

    Article  Google Scholar 

  24. Vespe M, Baker C, Griffiths H (2006) Aspect dependent drivers for multi-perspective target classification. Proc IEEE Conference on Radar, Verona, NY, 256–260. doi:10.1109/RADAR.2006.1631809

  25. Xiao Z, Xu J, Peng S, Mou S (2006) Super-resolution image restoration of a PMMW sensor based on POCS algorithm. Proc. 1st International Symposium on Systems and Control in Aerospace and Astronautics, Harbin, China, 680–683

  26. Youla DC, Webb H (1982) Image restoration by the method of convex projections: part 1-theory. IEEE Trans Med Imaging MI-1(2):81–94. doi:10.1109/TMI.1982.4307555

    Article  Google Scholar 

  27. Zhang HH, Nasrabadi NM, Zhang YN, Huang TS (2012) Multi-view automatic target recognition using joint sparse representation. IEEE Trans Aerosp Electron Syst 48(3):2481–2497. doi:10.1109/TAES.2012.6237604

    Article  Google Scholar 

  28. Zhao Q, Principe JC (2001) Support vector machines for SAR automatic target recognition. IEEE Trans Aerosp Electron Syst 37(2):643–654. doi:10.1109/7.937475

    Article  Google Scholar 

  29. Zhou J, Shi Z, Cheng X, Fu Q (2011) Automatic target recognition of SAR images based on global scattering center model. IEEE Trans Geosci Remote Sens 49(10):3713–3729. doi:10.1109/TGRS.2011.2162526

    Article  Google Scholar 

Download references

Acknowledgments

The work is supported by the National Natural Science Foundation of China (No. 61302129, No. 61204030), Zhejiang Provincial Natural Science Foundation of China (No. LY13F020030), Zhejiang Provincial Nonprofit Technology Research Projects (2014C31045) and China Scholarship Council.

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Correspondence to Ruohong Huan.

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Huan, R., Wang, C., Pan, Y. et al. New structure for multi-aspect SAR image target recognition with multi-level joint consideration. Multimed Tools Appl 75, 7519–7540 (2016). https://doi.org/10.1007/s11042-015-2674-6

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  • DOI: https://doi.org/10.1007/s11042-015-2674-6

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