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		题名	作者	年代	出处	被引量
	1	Improved non-negative tensor Tucker decomposition algorithm for interference hyper-spectral image compression显示文摘The compression method, first proposed in 2012, is based on the non-negative tensor decomposition for interference hyper-spectral image data. As a tensor is generated by a huge amount of interference hyper-spectral images, the multiplicative update algorithm is made extremely complicated, and even unfeasible.To reduce the computational cost and speed up the convergence, this paper, based on the characteristics of interference hyper-spectral images, develops a new algorithm using different down-sampling factors for different non-negative wavelet sub-band tensors. The experimental results showed that this algorithm could significantly shorten the running time, while maintaining a good compression performance compared with the conventional methods.	WEN Jia ZHAO JunSuo MA CaiWen WANG CaiLing	2015	Science China(Information Sciences)2015，58，5：	0

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