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[期刊论文]

Algorithm of spectral super-resolution of hyperspectral imagery based on redundant dictionary

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作者:

Wang, S.-Y. (Wang, S.-Y..) (学者:王淑莹) | Zhang, Z.-X. (Zhang, Z.-X..) | Wang, B. (Wang, B..) (学者:王波)

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Scopus PKU CSCD

摘要:

To enhance the spatial resolution of hyperspectral image, a hyperspectral image super-resolution restoration algorithm based on redundant dictionary was presented in this paper. By training a group of high and low resolution redundant dictionary, the corresponding image element curve of high and low resolution was made to have the same sparse representation coefficients in sparse decomposition based on redundant dictionary in this algorithm. During the process of super-resolution restoration, the low resolution of hyperspectral image sparse decomposes based on low resolution redundant dictionary. The high resolution image was reconstructed by using the sparse representation coefficients and the high resolution dictionary. The experimental results show that, compared with the image patch based sparse super resolution algorithm and the traditional image bilinear interpolation method, the PSNR of image reconstruction is significantly enhanced. The algorithm sparse decomposes the hyperspectral image along the spectral dimension to avoid the traditional algorithm problem of spectral distortion caused by restoration. The computational complexity of the algorithm is significantly reduced. ©, 2015, Beijing University of Technology. All right reserved.

关键词:

Hyperspectral imagery; Redundant dictionary; Sparse decomposition; Super-resolution restoration

作者机构:

  • [ 1 ] [Wang, S.-Y.]Beijing Engineering Research Center for IOT Software and System, College of Saft Ware Engineering, Beijing University of Technology, Beijing, 100124, China
  • [ 2 ] [Zhang, Z.-X.]Beijing Engineering Research Center for IOT Software and System, College of Saft Ware Engineering, Beijing University of Technology, Beijing, 100124, China
  • [ 3 ] [Wang, B.]Beijing Engineering Research Center for IOT Software and System, College of Saft Ware Engineering, Beijing University of Technology, Beijing, 100124, China

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来源 :

Journal of Beijing University of Technology

ISSN: 0254-0037

年份: 2015

期: 10

卷: 41

页码: 1522-1527

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