Improved bi-dimensional empirical mode decomposition based on 2D-assisted signals: Analysis and application

IET Image Processing

Volumn 5, Issue 3, 2011, Pages 205-221

  Xu, G L ^a   Wang, X T ^a   Xu, X G ^a  

^a DALIAN NAVAL ACADEMY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

BOUNDARY EFFECTS; EMPIRICAL MODE DECOMPOSITION; INTRINSIC MODE FUNCTIONS; ORIGINAL IMAGES;

GAUSSIAN NOISE (ELECTRONIC);

EID: 79959726027     PISSN: 17519659     EISSN: None     Source Type: Journal    
DOI: 10.1049/iet-ipr.2009.0158     Document Type: Article

References (45)

1. Huang, N.E., Shen, Z., and Long, S.R.: et al. 'The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis', Proc. R. Soc. Lond. A, 1998, 454, p. 903-99510.1098/rspa.1998.0193
2. Xu, G.L., Wang, X.T., and Xu, X.G.: et al. 'Image enhancement algorithm based on neighborhood limited empirical mode decomposition', Acta Electron. Sin., 2006, 34, (3), p. 99-1030372-2112
3. Xu, G.L., Wang, X.T., and Xu, X.G.: 'Neighborhood limited empirical mode decomposition and application in image processing', IEEE Proc. ICIG, 2007, p. 149-154
4. Xu, G.L., Wang, X.T., Xu, X.G., and Zhu, T.: 'Multi-band image fusion algorithm based on neighborhood limited empirical mode decomposition', J. Infrared Millim. Waves, 2006, 25, (3), p. 225-2281001-9014
5. Wu, Z., and Huang, N.E.: 'A study of the characteristics of white noise using the empirical mode decomposition method', Proc. R. Soc. Lond. A, 2004, 460, p. 1597-161110.1098/rspa.2003.1221
6. Xu, G.L., Wang, X.T., and Xu, X.G.: et al. 'The conditions and principle for the direct decomposition from multi-component to mono-component using EMD', Prog. Nat. Sci. China, 2006, 16, (10), p. 1356-1360 (in Chinese)
7. Huang, N.E., Shen, Z., and Long, S.R.: 'A new view of nonlinear water waves: the Hilbert spectrum', Annu. Rev. Fluid Mech., 1999, 31, p. 417-457
8. Deering, R., and Kaiser, J.F.: 'The use of a masking signal to improve empirical mode decomposition', IEEE ICASSP, 2005, p. IV-485-488
9. Senroy, N., and Suryanarayanan, S.: 'Two techniques to enhance empirical mode decomposition for power quality applications', IEEE, Power Engineering Society General Meeting, Tampa, FL, USA 2007, p. 1-6
10. Senroy, N., Suryanarayanan, S., and Ribeiro, P.F.: 'An improved Hilbert-Huang method for analysis of time-varying waveforms in power quality', IEEE Trans. Power Syst., 2007, 22, (4), p. 1843-185010.1109/TPWRS.2007.907542 0885-8950
11. Gledhill, R.J.: 'Methods for investigating conformational change in biomolecular simulations', A Dissertation for the degree of Doctor of Philosophy at Department of Chemistry, the University of Southampton, 2003, p. 201
12. Flandrin, P., Gonçalvès, P., and Rilling, G.: 'EMD equivalent filter banks, from interpretation to applications', Huang, N.E., Shen, S.S.P., 'Hilbert-Huang transform: introduction and applications'(World Scientific, Singapore 2005), p. 67-87p. 360
13. 'Ensemble empirical mode decomposition: a noise assisted data analysis method', COLA Technical Report, 2005 Available at: ftp://grads.iges.org/pub/ctr/ctr_193.pdf
14. Flandrin, P., Rilling, G., and Gonçalvès, P.: 'Empirical mode decomposition as a filter bank', IEEE Signal Process. Lett., 2004, 11, p. 112-11410.1109/LSP.2003.821662 1070-9908
15. Rilling, G., and Flandrin, P.: 'One or two frequencies? The empirical mode decomposition answers', IEEE Trans. Signal Process., 2008, 56, (1), p. 85-951053-587X
16. Xu, G.L., Wang, X.T., and Xu, X.G.: 'Neighborhood limited empirical mode decomposition and application in image processing', Fourth Int. Conf. on Image and Graphics, Chengdu of China 2007, p. 149-154
17. Cheng, J., Yu, D., and Yang, Y.: 'A fault diagnosis approach for roller bearings based on EMD method and AR model', Mech. Syst. Signal Process., 2006, 20, p. 350-3620888-3270
18. Han, C., Wang, G.H., and Fan, C.D.: 'A novel method to reduce speckle in SAR images', Int. J. Remote Sens., 2002, 23, (23), p. 5095-51010143-1161
19. Yue, H.Y., Guo, H.D., and Han, C.M.: et al. 'A SAR interferogram filter based on the empirical mode decomposition method', Geoscience and Remote Sensing Symp., 2001, 5, p. 2061-206310.1109/IGARSS.2001.977903
20. Nunes, J.C., Niang, O., and Bouaoune, Y.: et al. 'Texture analysis based on the bidimensional empirical mode decomposition with gray-level co-occurrence models', IEEE Mach. Vis. Appl., 2003, 2, p. 633-63510.1109/ISSPA.2003.1224962
21. Yang, Z.H., Qi, D.X., and Yang, L.H.: 'Signal period analysis based on Hilbert-Huang transform and its application to texture analysis', IEEE Proc. Third Int. Conf. on Image and Graphics, 2004, p. 430-433
22. Xiong, C.Z., Xu, J.Y., Zou, J.C., and Qi, D.X.: 'Texture classification based on EMD and FFT', J. Zhejiang Univ. Sci. A, 2006, 7, (9), p. 1516-152110.1631/jzus.2006.A1516
23. Nunes, J.C., Guyot, S., and Delechelle, E.: 'Texture analysis based on local analysis of the bidimensional empirical mode decomposition', Mach. Vis. Appl., 2005, 16, p. 177-18810.1007/s00138-004-0170-5
24. Liu, Z.X., and Peng, S.L.: 'The directional empirical mode decomposition and application in texture segmentation', Chin. Sci. E, 2005, 35, (2), p. 113-123
25. Liu, Z.X., Wang, H.J., and Peng, S.L.: 'Texture segmentation using directional empirical mode decomposition', Proc. 17th Int. Conf. on Pattern Recognition, 2004, p. 279-282
26. Bulow, T., and Sommer, G.: 'Hypercomplex signals-a novel extension of the analytic signal to the multidimensional case', IEEE Trans. Signal Process., 2001, 49, (11), p. 2844-285210.1109/78.960432 1053-587X
27. Gonzalez, C.R., and Richard Woods, E.: 'Digital image processing', 2nd(Pearson Education 2003)
28. Chaudhuri, B.B., and Sarkar, N.: 'Texture segmentation using fractal dimension [J]', IEEE Trans. Pattern Anal. Mach. Intell., 1995, 17, (1), p. 72-7710.1109/34.368149 0162-8828
29. Tuceryan, M., and Jain, A.K.: 'Texture segmentation using Voronoi polygons', IEEE Trans. Pattern Anal. Mach. Intell., 1990, 12, (2), p. 211-21610.1109/34.44407 0162-8828
30. Comer, M.L., and Delp, E.J.: 'Segmentation of textured images using a multiresolution Gaussian autoregressive model', IEEE Trans. Image Process., 1999, 8, p. 408-42010.1109/83.748895 1057-7149
31. Burt, P.J., and Adelson, E.H.: 'The laplacian pyramid as a compact image code', IEEE Trans. Commun., 1983, COM-3l, (4), p. 532-54010.1109/TCOM.1983.1095851 0090-6778
32. Liu, Z., and Peng, S.: 'Boundary processing of bidimensional using texture synthesis', IEEE Signal Process. Lett., 2005, 12, (1), p. 33-361070-9908
33. Xu, G.L., Wang, X.T., and Xu, X.G.: 'Improved bi-dimensional EMD and Hilbert spectrum for the analysis of textures', Pattern Recognit., 2009, 42, (5), p. 718-7340031-3203
34. Sharif Bhuiyan, M.A., Adhami, R.R., and Khan, J.F.: 'Fast and adaptive bidimensional empirical mode decomposition using order-statistics filter based envelope estimation', EURASIP J. Adv. Signal Process., 2008, p. 728356 p. 1810.1155/2008/728356
35. Sabri, A., Karoud, M., Tairi, H., and Aarab, A.: 'Fast bidimensional empirical mode decomposition based on an adaptive block partitioning', International J. Comput. Sci. Netw. Secur., 2008, 8, (11), p. 357-363
36. Hariharan, H., Gribok, A., Abidi, M., and Koschan, A.: 'Image fusion and enhancement via empirical mode decomposition', J. Pattern Recognit. Res., 2006, 1, (1), p. 16-32
37. http://www.mathworks.com/products/matlab/
38. Gonzalez, C.R., Woods, E.R., and Eddins, L.S.: 'Digital image processing using MATLAB', (Prentice Hall, USA 2004)
39. da Cunha, A.L., Zhou, J., and Do, M.N.: 'The nonsubsampled contourlet transform: theory, design, and applications', IEEE Trans. Image Process., 2006, 15, (10), p. 3089-310110.1109/TIP.2006.877507 1057-7149
40. Velde, K.V.: 'Multi-scale color image enhancement', Proc. Int. Conf. Image Processing, 1999, 3, p. 584-58710.1109/ICIP.1999.817182
41. Starck, J., Murtagh, F., Candès, E.J., and Donoho, D.L.: 'Gray and color image contrast enhancement by the Curvelet transform', IEEE Trans. Image Process., 2003, 12, (6), p. 706-71710.1109/TIP.2003.813140 1057-7149
42. Rahman, Z., Jobson, D.J., and Woodell, G.A.: 'Multi-scale retinex for color image enhancement', IEEE Int. Conf. Image Processing, 1996, 3, p. 1003-100610.1109/ICIP.1996.560995
43. Land, E.: 'Recent advances in retinex theory', Vis. Res., 1986, 26, (1), p. 7-2110.1016/0042-6989(86)90067-2 0042-6989
44. Jobson, D.J., Rahman, Z., and Woodell, G.A.: 'Properties and performance of a center/surround retinex', IEEE Trans. Image Process., 1997, 6, p. 451-46210.1109/83.557356 1057-7149
45. Munteanu, C., and Rosa, A.: 'Color image enhancement using evolutionary principles and the retinex theory of color constancy', Proc. 2001 IEEE Signal Processing Society Workshop on Neural Networks for Signal Processing XI, 2001, p. 393-402