Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

CP tensor-based compression of hyperspectral images

Not Accessible

Your library or personal account may give you access

Abstract

In this paper, an effective CANDECOMP/PARAFAC tensor-based compression (CPTBC) approach is proposed for on-ground hyperspectral images (HSIs). By considering the observed HSI cube as a whole three-order tensor, the proposed CPTBC method utilizes the CANDECOMP/PARAFAC tensor decomposition to decompose the original HSI data into the sum of R rank-1 tensors, which can simultaneously exploit both the spatial and spectral information of HSIs. Specifically, compared with the original HSI data, the R rank-1 tensors have fewer non-zero entries. In addition, non-zero entries of the R rank-1 tensors are sparse and follow a regular distribution. Therefore, the HSI can be efficiently compressed into R rank-1 tensors with the proposed CPTBC method. Our experimental results on real three HSIs demonstrate the superiority of the proposed CPTBC method over several well-known compression approaches and the average PSNR improvements of the proposed method over the six compared methods (i.e., MPEG4, band-wise JPEG2000, TD, 3D-SPECK, 3D-TCE, 3D-TARP) are more than 13, 10, 6, 4, 3, and 3 dB, respectively.

© 2017 Optical Society of America

Full Article  |  PDF Article
More Like This
Compression of hyperspectral images based on Tucker decomposition and CP decomposition

Lei Yang, Jinsong Zhou, Juanjuan Jing, Lidong Wei, Yacan Li, Xiaoying He, Lei Feng, and Boyang Nie
J. Opt. Soc. Am. A 39(10) 1815-1822 (2022)

Hyperspectral image denoising using the robust low-rank tensor recovery

Chang Li, Yong Ma, Jun Huang, Xiaoguang Mei, and Jiayi Ma
J. Opt. Soc. Am. A 32(9) 1604-1612 (2015)

Tensor decomposition-based sparsity divergence index for hyperspectral anomaly detection

Lili Zhang and Chunhui Zhao
J. Opt. Soc. Am. A 34(9) 1585-1594 (2017)

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Figures (8)

You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Tables (1)

You do not have subscription access to this journal. Article tables are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Equations (13)

You do not have subscription access to this journal. Equations are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All Rights Reserved