TY - JOUR
T1 - Deblurring and sparse unmixing for hyperspectral images
AU - Zhao, Xi Le
AU - Wang, Fan
AU - Huang, Ting Zhu
AU - Ng, Kwok Po
AU - Plemmons, Robert J.
N1 - Copyright:
Copyright 2013 Elsevier B.V., All rights reserved.
PY - 2013/7
Y1 - 2013/7
N2 - The main aim of this paper is to study total variation (TV) regularization in deblurring and sparse unmixing of hyperspectral images. In the model, we also incorporate blurring operators for dealing with blurring effects, particularly blurring operators for hyperspectral imaging whose point spread functions are generally system dependent and formed from axial optical aberrations in the acquisition system. An alternating direction method is developed to solve the resulting optimization problem efficiently. According to the structure of the TV regularization and sparse unmixing in the model, the convergence of the alternating direction method can be guaranteed. Experimental results are reported to demonstrate the effectiveness of the TV and sparsity model and the efficiency of the proposed numerical scheme, and the method is compared to the recent Sparse Unmixing via variable Splitting Augmented Lagrangian and TV method by Iordache
AB - The main aim of this paper is to study total variation (TV) regularization in deblurring and sparse unmixing of hyperspectral images. In the model, we also incorporate blurring operators for dealing with blurring effects, particularly blurring operators for hyperspectral imaging whose point spread functions are generally system dependent and formed from axial optical aberrations in the acquisition system. An alternating direction method is developed to solve the resulting optimization problem efficiently. According to the structure of the TV regularization and sparse unmixing in the model, the convergence of the alternating direction method can be guaranteed. Experimental results are reported to demonstrate the effectiveness of the TV and sparsity model and the efficiency of the proposed numerical scheme, and the method is compared to the recent Sparse Unmixing via variable Splitting Augmented Lagrangian and TV method by Iordache
KW - Alternating direction methods
KW - deblurring
KW - hyperspectral imaging
KW - linear spectral unmixing
KW - total variation (TV)
UR - http://www.scopus.com/inward/record.url?scp=84880280725&partnerID=8YFLogxK
U2 - 10.1109/TGRS.2012.2227764
DO - 10.1109/TGRS.2012.2227764
M3 - Journal article
AN - SCOPUS:84880280725
SN - 0196-2892
VL - 51
SP - 4045
EP - 4058
JO - IEEE Transactions on Geoscience and Remote Sensing
JF - IEEE Transactions on Geoscience and Remote Sensing
IS - 7
M1 - 6423278
ER -