Remote sensing image fusion based on Non-subsampled Dual-tree Complex Contourlet Transform and sparse representation

被引：0

作者：

Yin M. ^{[1
]}

Pang J.-Y. ^{[1
]}

Wei Y.-Y. ^{[1
]}

Duan P.-H. ^{[1
]}

机构：

[1] School of mathermatics, Hefei University of Technology, Hefei

来源：

Guangzi Xuebao/Acta Photonica Sinica | 2016年 / 45卷 / 01期

基金：

中国国家自然科学基金;

关键词：

Image processing; Non-subsampled dual-tree complex contourlet transform; Pulse coupled neural network; Remote sensing image fusion; Sparse representation; Sum-modified Laplacian;

D O I：

10.3788/gzxb20164501.0110002

中图分类号：

学科分类号：

摘要：

In order to improve the fusion quality of multispectral image and panchromatic image, a remote sensing image fusion algorithm was proposed based on Non-subsampled Dual-tree Complex Contourlet Transform (NSDTCT) and sparse representation. Firstly, the Intensity-Hue-Saturation (IHS) transform was applied to the multispectral image. Then, the histogram matching and smoothing filter-based intensity modulation were used to handle intensity component and panchromatic image. Secondly, the NSDTCT was employed to decompose the new intensity component and panchromatic image, and the low frequency coefficients and high frequency coefficients were obtained. For the low frequency coefficients, a fusion method based on sparse representation was presented, and the fused coefficients were obtained by combining spatial frequency with l1-norm maximum. For the high frequency coefficients, the sum-modified Laplacian was used for the external input of Pulse Coupled Neural Network (PCNN), and a fusion method based on the theory of improved PCNN was presented. Finally, the fused image was obtained by inverse NSDTCT and inverse IHS transform. The experimental results show that the proposed algorithm can improve the spatial resolution and maintain the spectral characteristics simultaneously, and outperforms other classical fusion algorithms in terms of both the visual quality and objective evaluation. © 2016, Science Press. All right reserved.

引用

页数：8

共 27 条

[1]

Choi M., A new intensity-hue-saturation fusion approach to image fusion with a tradeoff parameter, IEEE Transactions on Geoscience and Remote Sensing, 44, 6, pp. 1672-1682, (2006)

[2]

Rahmani S., Strait M., Merkurjev D., Et al., An adaptive IHS pan-sharpening method, IEEE Geoscience and Remote Sensing Letters, 7, 4, pp. 746-750, (2010)

[3]

Yang W., Wang J., Guo J., Et al., A novel algorithm for satellite images fusion based on compressed sensing and PCA, Mathematical Problems in Engineering, 3, pp. 206-226, (2013)

[4]

Wu J., Huang H.L., Qiu Y., Et al., Remote sensing image fusion based on average gradient of wavelet transform, Proceedings of the 2005 IEEE International Conference on Mechatronics and Automation, 4, pp. 1817-1821, (2005)

[5]

Amolins K., Zhang Y., Dare P., Wavelet based image fusion techniques-An introduction, review and comparison, ISPRS Journal of Photogrammetry and Remote Sensing, 62, 4, pp. 249-263, (2007)

[6]

Do M.N., Vetterli M., The contourlet transform: an efficient directional multiresolution image representation, IEEE Transactions on Image Processing, 14, 12, pp. 2091-2106, (2005)

[7]

Song M.-X., Guo P., A combinatorial optimization method for remote sensing image fusion with contourlet and HSI transform, Journal of Computer-Aided Design & Computer Graphics, 24, 1, pp. 83-88, (2012)

[8]

Da Cunha A.L., Zhou J., Do M.N., The nonsubsampled contourlet transform: theory, design, and applications, IEEE Transactions on Image Processing, 15, 10, pp. 3089-3101, (2006)

[9]

Liu H., Zhou K.-F., Wang J.-L., Et al., Remote sensing image fusion based on an improved NSCT and IHS transformation, Journal of Image and Graphics, 19, 2, pp. 322-327, (2014)

[10]

Wu Y.-Q., Shen Y., Yin J., Remote sensing image fusion based on improved gradient projection NMF and complex contourlet transform, Acta Photonica Sinica, 43, 5, (2014)

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