全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

快速离散Curvelet变换域的图像融合

DOI: 10.11834/jig.20150208

Keywords: 图像融合,快速离散Curvelet变换,局部能量,改进拉普拉斯能量和

Full-Text   Cite this paper   Add to My Lib

Abstract:

目的单一图像往往难以捕获一个场景下所有的细节信息,针对这一问题,可以通过多传感器或同一传感器的不同方式来获取多幅图像,然后通过图像融合技术将获得的多幅图像进行融合.为了提高图像融合的质量,提出一种基于快速离散Curvelet变换(FDCT)的图像融合新方法.方法不同于以往的方法,提出一组新的融合规则.分别采用基于局部能量和改进拉普拉斯能量和的方法,通过对FDCT分解得到的低频和高频系数进行系数选择,然后对得到的融合系数进行FDCT逆变换重构得到融合图像.结果通过对大量的多模态医学图像、红外可见光图像以及多聚焦图像进行图像融合实验,无论是运用视觉的主观评价,还是均值、标准差、信息熵以及边缘信息保持度等客观评价标准,本文方法都优于传统的基于像素平均、小波变换、FDCT以及双边梯度等融合方法.结论对比现有的方法,本文方法对多模态和多聚焦等形式的图像融合都表现出优越的融合性能.

References

[1]  Bai X, Zhou F, Xue B. Edge preserved image fusion based on multiscale toggle contrast operator [J]. Image and Vision Computing, 2011, 29(12):829-839.
[2]  Li S, Kang X, Hu J. Image fusion with guided filtering [J]. IEEE Transactions on Image Processing, 2013, 22(7):2864-2875.
[3]  Miles B, Ayed I B, Law M W K, et al. Spine image fusion via graph cuts [J]. IEEE Transactions on Biomedical Engineering, 2013, 60(7): 1841-1850.
[4]  Liang J, He Y, Liu D, et al. Image fusion using higher order singular value decomposition [J]. IEEE Transactions on Image Processing, 2012, 21(5): 2898-2909.
[5]  Yu N, Qiu T, Bi F, et al. Image features extraction and fusion based on joint sparse representation [J]. IEEE Journal of Selected Topics in Signal Processing,2011,5(5):1074-1082.
[6]  Ellmauthaler A, Pagliari C L, Da Silva E A B. Multiscale image fusion using the undecimated wavelet transform with spectral factorization and nonorthogonal filter banks [J]. IEEE Transactions on Image Processing, 2013, 22(3): 1005-1017.
[7]  Liu Y, Jin J, Wang Q. Region level based multi-focus image fusion using quaternion wavelet and normalized cut [J]. Signal Processing, 2014, 97(4): 9-30.
[8]  Pradhan P S, King R L, Younan N H, et al. Estimation of the number of decomposition levels for a wavelet-based multiresolution multisensor image fusion [J]. IEEE Transactions on Geoscience and Remote Sensing, 2006, 44(12): 3674-3686.
[9]  Zhang Z, Blum R S. A categorization of multiscale-decomposition-based image fusion schemes with a performance study for a digital camera application [J]. Proceeding of the IEEE,1999, 87(8): 1315-1326.
[10]  Li S T, Wang Y N, Zhang C F. Feature of human vision system based multi-focus image fusion [J]. Acta Electronica Sinica, 2001, 29(12):1699-1701. [李树涛,王耀南,张昌凡. 基于视觉特性的多聚焦图像融合[J]. 电子学报,2001,29(12):1699-1701.]
[11]  Elbanby G, El Madbouly E, Abdalla A. Fuzzy principal component analysis for sensor fusion [C]//Proceedings of the IEEE 11th International Conference on Information Science, Signal Processing and their Applications. Montreal, Canada: IEEE, 2012:442-447.
[12]  Wang L, Lu D, Lv J F. Multi-focus image fusion scheme based on wavelet contrast [J]. Journal of Image and Graphics, 2008, 13(1):145-150. [王丽,卢迪,吕剑飞.一种基于小波方向对比度的多聚焦图像融合方法[J]. 中国图象图形学报,2008,13(1):145-150.][DOI:10.11834/jig.20080126]
[13]  Aiazzi B, Alparone L, Barducci A, et al. Multispectral fusion of multisensor image data by the generalized Laplacian pyramid [C]//IEEE International Conference on Geoscience and Remote Sensing Symposium. Hamburg: BRD, 1999: 1183-1185.
[14]  Petrovic V S, Xydeas C S. Gradient-based multiresolution image fusion [J]. IEEE Transactions on Image Processing, 2004, 13(2): 228-237.
[15]  Chipman L J, Orr T M, Graham L N. Wavelets and image fusion [C]//Proceedings of IEEE International Conference on Image Processing. Washington D C, America: IEEE, 1995: 248-251.
[16]  Yang Y, Park D S, Huang S, et al. Medical image fusion via an effective wavelet based approach [J]. EURASIP Journal on Advances in Signal Processing, 2010, 2010, 44:1-13.
[17]  Qu X B, Yan J W, Yang G D. Multifocus image fusion method of sharp frequency localized contourlet transform domain based on sum-modified-laplacian [J]. Optics and Precision Engineering, 2009, 17(5):1203-1211. [屈小波,闫敬文,杨贵德. 改进拉普拉斯能量和的尖锐频率局部化Contourlet域多聚焦图像融合方法[J]. 光学精密工程, 2009, 17(5): 1203-1211.]
[18]  Candès E J, Donoho D L. Curvelets: a surprisingly effective nonadaptive representation for objects with edges [R]. California: Stanford university department of Statistics, 2000.
[19]  Candès E J, Donoho D L. Recovering edges in ill-posed inverse problems: optimality of curvelet frames [J]. The Annals of Statistics, 2002, 30(3): 784-842.
[20]  Candès E J, Demanet L, Donoho D L, et al. Fast discrete curvelet transforms [J]. Muticale Modeling and Simulation. 2006, 5(3):861-899.
[21]  更多...
[22]  Li H F, Chai Y, Zhang X Y. Multifocus image fusion algorithm based on multiscale products and property of human visual system [J]. Control and Decision, 2012, 27(3):355-361. [李华锋,柴毅,张晓阳. 基于多尺度积视觉特性的多聚焦图像融合算法[J]. 控制与决策,2012,27(3):355-361.]
[23]  Li H, Guo L, Liu H. Research on image fusion based on the second generation curvelet transform [J]. Acta Optica Sinica, 2006,26(5):657-662. [李晖晖,郭雷,刘航. 基于二代curvelet变换的图像融合研究[J]. 光学学报,2006,26(5):657-662.].
[24]  Guo M, Fu Z, Xi X L. Novel fusion algorithm for infrared and visible images based on local energy in NSCT domain[J]. Infrared and Laser Engineering, 2012, 41(8): 2229-2235.[郭明,符拯,奚晓梁.基于局部能量的NSCT域红外与可见光图像融合算法[J].红外与激光工程,2012, 41(8): 2229-2235.]
[25]  Nayar S K, Nakagawa Y. Shape from focus [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1994, 16(8):824-831.
[26]  Zhang X, Li X, Feng Y. A new image fusion performance measure using Riesz transforms [J]. Optik-International Journal for Light and Electron Optics, 2014, 125(3):1427-1433.
[27]  Xydeas C S, Petrovi? V. Objective image fusion performance measure [J]. Electronics Letters, 2000, 36(4):308-309.
[28]  Tian J, Chen L, Ma L, et al. Multi-focus image fusion using a bilateral gradient-based sharpness criterion[J]. Optics Communications, 2011, 284(1):80-87.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133