Technique for image fusion based on NSST domain and human visual characteristics

被引：0

作者：

Kong, Weiwei ^{[1
,2
]}

Lei, Yingjie ^{[2
]}

机构：

[1] Department of Information Engineering, Engineering University of Armed Police Force

[2] Missile Institute, Air Force Engineering University

来源：

Harbin Gongcheng Daxue Xuebao/Journal of Harbin Engineering University | 2013年 / 34卷 / 06期

关键词：

Human visual characteristic; Image fusion; Non-subsampled shearlet transform; Visual sensitivity coefficient;

D O I：

10.3969/j.issn.1006-7043.201209029

中图分类号：

学科分类号：

摘要：

A novel technique for image fusion based on the non-subsampled shearlet transform (NSST) domain and human visual characteristic (HVC) is proposed to resolve the problem of the multi-sensor image fusion. Multi-scale and multi-directional sparse decompositions of source images are performed by NSST, so that the low-frequency sub-images and a series of high-frequency ones with diverse scales and directions can be obtained. Then, as the evaluation norm of sub-images fusion, the definition of visual sensitivity coefficient is presented to complete the fusion process of sub-images from each corresponding source image, respectively. Meanwhile, the algorithm for image fusion based on NSST and HVC is devised. The final fused image is achieved by utilizing inverse NSST to all fused sub-images. Experimental results show that the technique proposed has better performance, and higher running efficiency.

引用

页码：777 / 782

页数：5

共 27 条

[1]

pp. 45-76, (2007)

[2]

Chen C., Li W., Chen L., Et al., An adaptive biomimetic image processing method: LDRF algorithm, CAAI Transactions on Intelligent Systems, 7, 5, pp. 404-408, (2012)

[3]

Jiang F., Guo M., Liu S., Et al., Quality assessment of stereoscopic images based on the significance of perceptual vision, CAAI Transactions on Intelligent Systems, 7, 5, pp. 414-422, (2012)

[4]

Wang J., Yuan X., Liu Z., An extraction method of pupil and corneal reflection centers based on image processing technology, CAAI Transactions on Intelligent Systems, 7, 5, pp. 423-428, (2012)

[5]

Miao Q., Wang B., A novel image fusion algorithm based on local contrast and adaptive PCNN, Chinese Journal of Computers, 31, 5, pp. 875-880, (2008)

[6]

Ma Y., Lin D., Wang Z., Et al., Multi-focus image fusion using PCNN and rough set, Journal of University of Electronic Science and Technology of China, 38, 4, pp. 485-488, (2009)

[7]

Kong W., Lei Y., Lei Y., Et al., Image fusion technique based on NSCT and adaptive unit-fast-linking PCNN, IET Image Processing, 5, 2, pp. 113-121, (2011)

[8]

Do M.N., Vetterli M., The finite ridgelet transform for image representation, IEEE Transactions on Image Processing, 12, 1, pp. 16-28, (2003)

[9]

Candes E.J., Donoho D.L., Curvelets: a surprisingly effective non-adaptive representation for objects with edges, Saint-Malo Proceedings, (2002)

[10]

Do M.N., Vetterli M., The contourlet transform: an efficient directional multi-resolution image representation, IEEE Transactions on Image Processing, 11, 1, pp. 16-28, (2002)

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