Multi-focus image fusion using dual-tree contourlet and compressed sensing

Guangdian Gongcheng/Opto-Electronic Engineering

Volumn 38, Issue 4, 2011, Pages 87-94

  Jin, Wei ^a   Fu, Ran Di ^a   Ye, Ming ^a   Li, Jin Xiang ^a  

^a NINGBO UNIVERSITY   (China)

Author keywords

Compressed sensing; Dual tree Contourlet; Image fusion; Multi focus image; Two step iterative shrinkage threshold algorithm

Indexed keywords

EID: 79957904367     PISSN: 1003501X     EISSN: None     Source Type: Journal    
DOI: 10.3969/j.issn.1003-501X.2011.04.016     Document Type: Article

References (15)

1. Ma H, Jia C, Liu S. Multisource image fusion based on wavelet transform[J]. International Journal of Information Technology(S0218-7957), 2005, 11(7): 81-91.
2. De I, Chanda B. A simple and efficient algorithm for multifocus image fusion using morphological wavelets[J]. Signal Processing(S0165-1684), 2006, 86: 924-936.
3. Minh N D, Martin V. The contourlet transform: an efficient directinal multiresolution image representation[J]. IEEE Trans. on Image Processing(S1057-7149), 2005, 14(12): 2091-2106.
4. Yue L, Minh N D. A new contourlet transform with sharp frequency localization[C]// Proceedings of the IEEE International Conference on Image Processing, Atlanta, USA, Oct 8-11, 2006: 1629-1632.
5. CHEN Xin-wu, GONG Jun-bin, LIU Wei, et al. Image Denoising Based on Complex Contourlet Transform[J]. Opto-Electronic Engineering, 2009, 36(10): 111-115.
6. Nguyen T T, Oraintara S. The shiftable complex directional pyramid: Theoretical aspects[J]. IEEE Trans. on Signal Processing(S1053-587X), 2008, 56(10): 4651-4659.
7. Selesnick I W, Baraniuk R G, Kingsbury N G. The dual-tree complex wavelet transform[J]. IEEE Signal Processing Magazine(S1053-5888), 2005, 22(6): 123-151.
8. Candes E, Wakin M B. An introduction to compressive sampling[J]. IEEE Signal Processing Magazine(S1053-5888), 2008, 48(4): 21-30.
9. Provost F, Lesage F. The application of compressed sensing for photo-acoustic tomography[J]. IEEE Trans. on Med. Imaging(S0278-0062), 2009, 28(4): 585-594.
10. Donoho D L, Tsaig Y, Drori I, et al. Sparse solution of underdetermined linear equations by stagewise orthogonal matching pursuit[EB/OL].(2006-12)[2010-5]. http://www.cs.tau.ac.il/~idrori/StOMP.pdf.
11. Berinde R, Indyk P. Sparse recovery using sparse random matrices[EB/OL]. (2008-3)[2010-5]. http://people.csail.mit.edu/indyk/report.pdf.
12. Donoho D L. For most large underdetermined systems of linear equations, the minimal ell-1 norm near-solution approximates the sparsest near-solution[J]. Communications on Pure and Applied Mathematics(S0010-3640), 2006, 59(7): 907-934.
13. Daubechies I, Derise M. An interative thresholding algorithm for linear inverse problem with a sparsity constrain[J]. Communications on Pure and Applied Mathematics(S0010-3640), 2004, 57(11). 1413-1457.
14. Bioucas-dias J M, Figueirdo M A. A new TwIST: Two-Step Iterative Shrinkage/Thresholding algorithms for image restoration[J]. IEEE Trans. on Image processing(S1057-7149), 2007, 16(12): 2992-3004.
15. HAN Bing, WU Feng, WU Da-peng. Image representation by compressed sensing[C]// Proceedings of the International Conference on Image Processing, San Diego, USA, Oct 12-15, 2008: 1344-1347.