Compression of Interference Hyperspectral Image Based on FHALS-NTD

	Compression of Interference Hyperspectral Image Based on FHALS-NTD
	Du L. M.; Li J.; Jin G.; Gao H. B.; Jin L. X.; Zhang K.
	2012
发表期刊	Spectroscopy and Spectral Analysis
ISSN	1000-0593
卷号	32 期号:11 页码:3155-3160
摘要	A hyperspectral interference image compression algorithm based on fast hierarchical alternating least squares non-negative tensor Tucker decomposition (FHALS-NTD) is proposed. Firstly, the interference hyperspectral image is decomposed by 3-D OPD lifting-based discrete wavelet transform (3D OPT-LDWT) in the OPD direction. Then, the 3D DWT sub-bands decomposed are used as a three order nonnegative tensor, which is decomposed by the proposed FHALS-NTD algorithm to obtain 8 core tensors and 24 unknown component matrices. Finally, to obtain the final compressed bit-stream, each unknown component matrices element is quantized, and each core tensor is encoded by the proposed bit-plane coding of significant coefficients. The experimental results showed that the proposed compression algorithm could be used for reliable and stable work and has good compressive property. In the compression ratio range from 32 : 1 to 4 : 1, the average peak signal to noise ratio of proposed compression algorithm is higher than 40 dB. Compared with traditional approaches, the proposed method could improve the average PSNR by 1.23 dB. This effectively improves the compression performance of hyperspectral interference image.
收录类别	SCI
语种	中文
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/34054
专题	中科院长春光机所知识产出
推荐引用方式 GB/T 7714	Du L. M.,Li J.,Jin G.,et al. Compression of Interference Hyperspectral Image Based on FHALS-NTD[J]. Spectroscopy and Spectral Analysis,2012,32(11):3155-3160.
APA	Du L. M.,Li J.,Jin G.,Gao H. B.,Jin L. X.,&Zhang K..(2012).Compression of Interference Hyperspectral Image Based on FHALS-NTD.Spectroscopy and Spectral Analysis,32(11),3155-3160.
MLA	Du L. M.,et al."Compression of Interference Hyperspectral Image Based on FHALS-NTD".Spectroscopy and Spectral Analysis 32.11(2012):3155-3160.

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