Non-rigid image registration with dynamic Gaussian component density and space curvature preservation

IEEE Transactions on Image Processing

Volumn 28, Issue 5, 2019, Pages

  Yang, Zhuoqian ^a,b   Yang, Yang ^a   Yang, Kun ^a   Wei, Zi Quan ^a  

^a YUNNAN NORMAL UNIVERSITY   (China)

^b BEIHANG UNIVERSITY   (China)

Author keywords

dynamic Gaussian component density; feature matching; Image registration; non rigid; space curvature preservation

Indexed keywords

ANTENNAS; DAMAGE DETECTION; DETECTORS; DISASTERS; ESTIMATION; FEATURE EXTRACTION; FREQUENCY DOMAIN ANALYSIS; FREQUENCY ESTIMATION; GAUSSIAN DISTRIBUTION; IMAGE REGISTRATION; ITERATIVE METHODS; MEDICAL IMAGING; MILITARY APPLICATIONS;

FEATURE MATCHING; GAUSSIAN COMPONENTS; INDEXES; NON-RIGID; SPACE CURVATURES;

MILITARY PHOTOGRAPHY;

EID: 85058882231     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2018.2887204     Document Type: Article

References (67)

1. P. Zhou, G. Cheng, Z. Liu, S. Bu, and X. Hu, "Weakly supervised target detection in remote sensing images based on transferred deep features and negative bootstrapping," Multidimensional Syst. Signal Process., vol. 27, no. 4, pp. 925-944, 2016.
2. A. Sameer, S. Noah, S. Ian, S. M. Seitz, and R. Szeliski, "Building Rome in a day," in Proc. Int. Conf. Comput. Vis., 2009, pp. 72-79.
3. X. Shen, L. Xu, Q. Zhang, and J. Jia, "Multi-modal and multi-spectral registration for natural images," in Proc. Eur. Conf. Comput. Vis., 2014, pp. 309-324.
4. F. Song, M. Li, Y. Yang, K. Yang, X. Gao, and D. Ting, "Small UAV based multi-viewpoint image registration for monitoring cultivated land changes in mountainous terrain," Int. J. Remote Sens., vol. 39, no. 21, pp. 7201-7224, 2018.
5. F. Song et al., "Multi-scale feature based land cover change detection in mountainous terrain using multi-temporal and multisensor remote sensing images," IEEE Access, to be published, doi: 10.1109/ACCESS.2018.2883254.
6. K. Yang, Z. Yu, Y. Luo, Y. Yang, L. Zhao, and X. Zhou, "Spatial and temporal variations in the relationship between lake water surface temperatures and water quality-A case study of Dianchi lake," Sci. Total Environ., vol. 624, pp. 859-871, May 2018.
7. J. Ma, Y. Ma, and C. Li, "Infrared and visible image fusion methods and applications: A survey," Inf. Fusion, vol. 45, pp. 153-178, Jan. 2019.
8. A. Wong and D. A. Clausi, "ARRSI: Automatic registration of remotesensing images," IEEE Trans. Geosci. Remote Sens., vol. 45, no. 5, pp. 1483-1493, May 2007.
9. B. Zitová and J. Flusser, "Image registration methods: A survey," Image Vis. Comput., vol. 21, no. 11, pp. 977-1000, Oct. 2003.
10. R. Gonzalez and P. Wintz, Digital Image Processing, 2nd ed. Reading, MA, USA: Addison-Wesley, 1987.
11. J. Ma, J. Zhao, Y. Ma, and J. Tian, "Non-rigid visible and infrared face registration via regularized Gaussian fields criterion," Pattern Recognit., vol. 48, no. 3, pp. 772-784, 2015.
12. R. N. Bracewell, The Fourier Transform and Its Applications. New York, NY, USA: McGraw-Hill, 1986.
13. J. Ma, H. Zhou, J. Zhao, Y. Gao, J. Jiang, and J. Tian, "Robust feature matching for remote sensing image registration via locally linear transforming," IEEE Trans. Geosci. Remote Sens., vol. 53, no. 12, pp. 6469-6481, Dec. 2015.
14. J. Liang, X. Liu, K. Huang, X. Li, D. Wang, and X. Wang, "Automatic registration of multisensor images using an integrated spatial and mutual information (SMI) metric," IEEE Trans. Geosci. Remote Sens., vol. 52, no. 1, pp. 603-615, Jan. 2014.
15. D. G. Lowe, "Object recognition from local scale-invariant features," in Proc. IEEE Int. Conf. Comput. Vis., vol. 2. Sep. 1999, pp. 1150-1157.
16. C. Harris and M. Stephens, "A combined corner and edge detector," in Proc. Alvey Vis. Conf., Manchester, U.K., vol. 15, no. 50, 1988, pp. 5244-5210.
17. D. G. Lowe, "Distinctive image features from scale-invariant keypoints," Int. J. Comput. Vis., vol. 60, no. 2, pp. 91-110, 2004.
18. H. Bay, A. Ess, T. Tuytelaars, and L. Van Gool, "Speeded-up robust features (SURF)," Comput. Vis. Image Understand., vol. 110, no. 3, pp. 346-359, 2008.
19. H. Chui and A. Rangarajan, "A new point matching algorithm for nonrigid registration," Comput. Vis. Image Understand., vol. 89, nos. 2-3, pp. 114-141, Feb. 2003.
20. A. Myronenko and X. Song, "Point set registration: Coherent point drift," IEEE Trans. Pattern Anal. Mach. Intell., vol. 32, no. 12, pp. 2262-2275, Dec. 2010.
21. Y. Yang, S. H. Ong, and K. W. C. Foong, "A robust global and local mixture distance based non-rigid point set registration," Pattern Recognit., vol. 48, no. 1, pp. 156-173, 2015.
22. J. Ma, J. Zhao, and A. L. Yuille, "Non-rigid point set registration by preserving global and local structures," IEEE Trans. Image Process., vol. 25, no. 1, pp. 53-64, Jan. 2016.
23. S. Zhang, Y. Yang, K. Yang, Y. Luo, and S. H. Ong, "Point set registration with global-local correspondence and transformation estimation," in Proc. IEEE Int. Conf. Comput. Vis. (ICCV), Oct. 2017, pp. 2688-2696, doi: 10.1109/ICCV.2017.291.
24. J. Ma, J. Jiang, H. Zhou, J. Zhao, and X. Guo, "Guided locality preserving feature matching for remote sensing image registration," IEEE Trans. Geosci. Remote Sens., vol. 56, no. 8, pp. 4435-4447, Aug. 2018.
25. M. Gong, S. Zhao, L. Jiao, D. Tian, and S. Wang, "A novel coarseto-fine scheme for automatic image registration based on SIFT and mutual information," IEEE Trans. Geosci. Remote Sens., vol. 52, no. 7, pp. 4328-4338, Jul. 2014.
26. J. Fan, Y. Wu, F. Wang, Q. Zhang, G. Liao, and M. Li, "SAR image registration using phase congruency and nonlinear diffusion-based SIFT," IEEE Geosci. Remote Sens. Lett., vol. 12, no. 3, pp. 562-566, Mar. 2015.
27. K. Yang, A. Pan, Y. Yang, S. Zhang, S. H. Ong, and H. Tang, "Remote sensing image registration using multiple image features," Remote Sens., vol. 9, no. 6, pp. 581, 2017.
28. Z. Wei et al., "A small UAV based multi-temporal image registration for dynamic agricultural terrace monitoring," Remote Sens., vol. 9, no. 9, pp. 904, 2017.
29. Y. Xiang, F. Wang, and H. You, "OS-SIFT: A robust SIFT-like algorithm for high-resolution optical-to-SAR image registration in suburban areas," IEEE Trans. Geosci. Remote Sens., vol. 56, no. 8, pp. 3078-3090, Jun. 2018.
30. K. Mikolajczyk and C. Schmid, "A performance evaluation of local descriptors," IEEE Trans. Pattern Anal. Mach. Intell., vol. 27, no. 10, pp. 1615-1630, Oct. 2005.
31. E. Tola, V. Lepetit, and P. Fua, "DAISY: An efficient dense descriptor applied to wide-baseline stereo," IEEE Trans. Pattern Anal. Mach. Intell., vol. 32, no. 5, pp. 815-830, May 2010.
32. R. Bouchiha and K. Besbes, "Automatic remote-sensing image registration using surf," Int. J. Comput. Theory Eng., vol. 5, no. 1, pp. 88, 2013.
33. I. Colomina and P. Molina, "Unmanned aerial systems for photogrammetry and remote sensing: A review," ISPRS J. Photogram. Remote Sens., vol. 92, pp. 79-97, Jun. 2014.
34. M. S. Patel, N. M. Patel, and M. S. Holia, "Feature based multiview image registration using SURF," in Proc. Int. Symp. Adv. Comput. Commun. (ISACC), Sep. 2015, pp. 213-218.
35. H. Lin, P. Du, W. Zhao, L. Zhang, and H. Sun, "Image registration based on corner detection and affine transformation," in Proc. 3rd Int. Congr. Image Signal Process. (CISP), vol. 5, Oct. 2010, pp. 2184-2188.
36. I. Misra, S. M. Moorthi, D. Dhar, and R. Ramakrishnan, "An automatic satellite image registration technique based on Harris corner detection and Random Sample Consensus (RANSAC) outlier rejection model," in Proc. 1st Int. Conf. Recent Adv. Inf. Technol.(RAIT), Mar. 2012, pp. 68-73.
37. Y. Ye and J. Shan, "A local descriptor based registration method for multispectral remote sensing images with non-linear intensity differences," ISPRS J. Photogramm. Remote Sens., vol. 90, pp. 83-95, Apr. 2014.
38. B. Biswas, A. Chakrabarti, and K. N. Dey, "Image registration method using Harris Corner and modified Hausdorff distance with near set," in Proc. IEEE 2nd Int. Conf. Recent Trends Inf. Syst. (ReTIS), Jul. 2015, pp. 393-398.
39. E. Rosten and T. Drummond, "Machine learning for high-speed corner detection," in Proc. Eur. Conf. Comput. Vis. Berlin, Germany: Springer, 2006, pp. 430-443.
40. M. Butenuth et al., "Integrating pedestrian simulation, tracking and event detection for crowd analysis," in Proc. IEEE Int. Conf. Comput. Vis. Workshops (ICCV Workshops), Nov. 2011, pp. 150-157.
41. B. Sirmacek and P. Reinartz, "Feature analysis for detecting people from remotely sensed images," J. Appl. Remote Sens., vol. 7, no. 1, pp. 073594, 2013.
42. M. Calonder, V. Lepetit, C. Strecha, and P. Fua, "BRIEF: Binary robust independent elementary features," in Proc. Eur. Conf. Comput. Vis. Springer, 2010, pp. 778-792.
43. E. Rublee, V. Rabaud, K. Konolige, and G. Bradski, "ORB: An efficient alternative to SIFT or SURF," in Proc. IEEE Int. Conf. Comput. Vis. (ICCV), Nov. 2011, pp. 2564-2571.
44. C. Aguilera, F. Barrera, F. Lumbreras, A. D. Sappa, and R. Toledo, "Multispectral image feature points," Sensors, vol. 12, no. 9, pp. 12661-12672, 2012. [Online]. Available: Http://www.mdpi.com/ 1424-8220/12/9/12661
45. J. Ma, J. Zhao, J. Jiang, H. Zhou, and X. Guo, "Locality preserving matching," Int. J. Comput. Vis., to be published, doi: 10.1007/s11263-018-1117-z.
46. Z. Zhang, "Iterative point matching for registration of free-form curves and surfaces," Int. J. Comput. Vis., vol. 13, no. 2, pp. 119-152, 1994.
47. B. Jian and B. Vemuri, "Robust point set registration using Gaussian mixture models," IEEE Trans. Pattern Anal. Mach. Intell., vol. 33, pp. 1633-1645, Aug. 2011.
48. J. Ma, J. Zhao, J. Tian, Z. Tu, and A. L. Yuille, "Robust estimation of nonrigid transformation for point set registration," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR), Jun. 2013, pp. 2147-2154.
49. A. Basu, I. R. Harris, N. L. Hjort, and M. C. Jones, "Robust and efficient estimation by minimising a density power divergence," Biometrika, vol. 85, no. 3, pp. 549-559, 1998.
50. J. Ma, J. Zhao, J. Tian, A. L. Yuille, and Z. Tu, "Robust point matching via vector field consensus," IEEE Trans. Image Process., vol. 23, no. 4, pp. 1706-1721, Apr. 2014.
51. S. Zhang, K. Yang, Y. Yang, and Y. Luo, "Nonrigid image registration for low-altitude SUAV images with large viewpoint changes," IEEE Geosci. Remote Sens. Lett., vol. 15, no. 4, pp. 592-596, Apr. 2018.
52. A. P. Dempster, N. M. Laird, and D. B. Rubin, "Maximum likelihood from incomplete data via the EM algorithm," J. Roy. Statist. Soc. B, Methodol., vol. 39, no. 1, pp. 1-38, 1977.
53. R. M. Neal and G. E. Hinton, "A view of the EM algorithm that justifies incremental, sparse, and other variants," in Learning in Graphical Models. Dordrecht, The Netherlands: Springer, 1998, pp. 355-368.
54. F. L. Bookstein, "Principal warps: Thin-plate splines and the decomposition of deformations," IEEE Trans. Pattern Anal. Mach. Intell., vol. 11, no. 6, pp. 567-585, Jun. 1989.
55. R. Horaud, F. Forbes, M. Yguel, G. Dewaele, and J. Zhang, "Rigid and articulated point registration with expectation conditional maximization," IEEE Trans. Pattern Anal. Mach. Intell., vol. 33, no. 3, pp. 587-602, Mar. 2011.
56. S. Belongie, J. Malik, and J. Puzicha, "Shape matching and object recognition using shape contexts," IEEE Trans. Pattern Anal. Mach. Intell., vol. 24, no. 4, pp. 509-522, Apr. 2002.
57. R. Jonker and A. Volgenant, "A shortest augmenting path algorithm for dense and sparse linear assignment problems," Computing, vol. 38, no. 4, pp. 325-340, Nov. 1987.
58. A. N. Tikhonov and V. Y. Arsenin, Solutions of Ill-Posed Problems. Washington, DC, USA: V.H. Winston & Sons, 1977.
59. A. L. Yuille and N. M. Grzywacz, "A mathematical analysis of the motion coherence theory," Int. J. Comput. Vis., vol. 3, no. 2, pp. 155-175, 1989.
60. S. Zhang, K. Yang, Y. Yang, Y. Luo, and Z. Wei, "Non-rigid point set registration using dual-feature finite mixture model and globallocal structural preservation," Pattern Recognit., vol. 80, pp. 183-195, Aug. 2018.
61. G. Hermosillo, C. Chefd'Hotel, and O. Faugeras, "Variational methods for multimodal image matching," Int. J. Comput. Vis., vol. 50, no. 3, pp. 329-343, 2002.
62. C. Liu, J. Yuen, A. Torralba, J. Sivic, and W. T. Freeman, "SIFT flow: Dense correspondence across different scenes," in Proc. Eur. Conf. Comput. Vis. Springer, 2008, pp. 28-42.
63. H. Yang, W.-Y. Lin, and J. Lu, "DAISY filter flow: A generalized discrete approach to dense correspondences," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Jun. 2014, pp. 3406-3413.
64. C. Hernandez-Matas, X. Zabulis, A. Triantafyllou, P. Anyfanti, S. Douma, and A. A. Argyros, "FIRE: Fundus image registration dataset," J. Model. Ophthalmol., vol. 1, no. 4, pp. 16-28, 2017.
65. W. Ma et al., "Remote sensing image registration with modified sift and enhanced feature matching," IEEE Geosci. Remote Sens. Lett., vol. 14, no. 1, pp. 3-7, Jan. 2017.
66. F. Dellinger, J. Delon, Y. Gousseau, J. Michel, and F. Tupin, "SAR-SIFT: A SIFT-like algorithm for SAR images," IEEE Trans. Geosci. Remote Sens., vol. 53, no. 1, pp. 453-466, Jan. 2015.
67. H.-R. Su and S.-H. Lai, "Non-rigid registration of images with geometric and photometric deformation by using local affine Fourier-moment matching," in Proc. CVPR, Jun. 2015, pp. 2874-2882