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基于光谱相似性的高光谱图像超分辨率算法

DOI: 10.3724/SP.J.1004.2014.02797, PP. 2797-2807

Keywords: 超分辨率,高光谱图像,光谱相似性,结构自相似性

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Abstract:

?光谱相似性是指高光谱图像中的大量像元具有相似光谱的性质.提出了一种基于光谱相似性的高光谱遥感图像超分辨率算法,利用遥感图像中广泛存在的结构自相似性提升图像的空间分辨率,利用高光谱图像的低维子空间性通过主成分分析降低光谱维数提高运算效率,利用具有相似光谱的像元构建光谱约束项保证重建图像光谱的准确性.该算法在将单波段图像超分辨率方法推广到处理具有数百、乃至上千波段的高光谱图像过程中,既保证了重建图像光谱的准确性,又具有较高的运算效率.实验表明,与双三次插值和基于稀疏表示与光谱正则化约束的高光谱图像超分辨率算法相比,该算法具有更高的空间分辨率提升能力和更好的光谱保真能力.

References

[1]  Landgrebe D. Hyperspectral image data analysis. IEEE Signal Processing Magazine, 2002, 19(1): 17-28
[2]  Akgun T, Altunbasak Y, Mersereau R M. Super-resolution reconstruction of hyperspectral images. IEEE Transactions on Image Processing, 2005, 14(11): 1860-1875
[3]  Guo Z H, Wittmana T, Osher S. L1 unmixing and its application to hyperspectral image enhancement. In: Proceedings of Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XV. Orlando, FL, USA: SPIE, 2009. 1-9
[4]  Zhao Y Q, Yang J X, Zhang Q Y, Song L, Cheng Y M, Pan Q. Hyperspectral imagery super-resolution by sparse representation and spectral regularization. EURASIP Journal on Advances in Signal Processing, 2011, 2011(1): 87
[5]  Pan Zong-Xu, Yu Jing, Hu Shao-Xing, Sun Wei-Dong. Single image super resolution based on multi-scale structural self-similarity. Acta Automatica Sinica, 2014, 40(4): 594-603(潘宗序, 禹晶, 胡少兴, 孙卫东. 基于多尺度结构自相似性的单幅图像超分辨率算法. 自动化学报, 2014, 40(4): 594-603)
[6]  Wang Z, Bovik A C, Sheikh H R, Simoncelli E P. Image quality assessment: from error visibility to structural similarity. IEEE Transactions on Image Processing, 2004, 13(4): 600-612
[7]  Shaw G, Manolakis D. Signal processing for hyperspectral image exploitation. IEEE Signal Processing Magazine, 2002, 19(1): 12-16
[8]  Wang Yi-Qun, Yan Chang-Xiang, Miao Chun-An. Choice of spectral-splitting modes in space-borne hyper-spectral imager. Chinese Journal of Optics and Applied Optics, 2009, 2(4): 304-308(汪逸群, 颜昌翔, 苗春安. 星载高分辨率超光谱成像仪分光方式的选择. 中国光学与应用光学, 2009, 2(4): 304-308)
[9]  Eismann M T, Hardie R C. Application of the stochastic mixing model to hyperspectral resolution enhancement. IEEE Transactions on Geoscience and Remote Sensing, 2004, 42(9): 1924-1933
[10]  Engan K, Aase S O, Husoy J H. Method of optimal directions for frame design. In: Proceedings of the 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Phoenix, AZ, USA: IEEE, 1999. 2443-2446
[11]  Aharon M, Elad M, Bruckstein A. K-SVD: an algorithm for designing overcomplete dictionaries for sparse representation. IEEE Transactions on Signal Processing, 2006, 54(11): 4311-4322
[12]  Elad M, Aharon M. Image denoising via sparse and redundant representations over learned dictionaries. IEEE Transactions on Image Processing, 2006, 15(12): 3736-3745
[13]  Daubechies I, Defrise M, De Mol C. An iterative thresholding algorithm for linear inverse problems with a sparsity constraint. Communications on Pure and Applied Mathematics, 2004, 57(11): 1413-1457

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