Results 201 to 210 of about 1,769,588 (220)

Hyperspectral Unmixing Using Sparsity-Constrained Deep Nonnegative Matrix Factorization With Total Variation

IEEE Transactions on Geoscience and Remote Sensing, 2018
Hyperspectral unmixing is an important processing step for many hyperspectral applications, mainly including: 1) estimation of pure spectral signatures (endmembers) and 2) estimation of the abundance of each endmember in each pixel of the image. In recent years, nonnegative matrix factorization (NMF) has been highly attractive for this purpose due to ...
Xin-Ru Feng, Heng-Chao Li 0001, Jun Li 0009, Qian Du 0001, Antonio Plaza, William J. Emery   +5 more
openaire   +1 more source

Hyperspectral Unmixing Based on Sparsity-Constrained Nonnegative Matrix Factorization with Adaptive Total Variation

IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019
Hyperspectral unmixing is a critical processing step for many remote sensing applications. Nonnegative matrix factorization (NMF) has drawn extensive attention in hyperspectral image analysis recently. Considering that the abundance matrix is generally sparse and smooth, we propose a sparsity-constrained NMF with adaptive total variation (SNMF-ATV ...
Xin-Ru Feng, Heng-Chao Li 0001, Rui Wang 0090   +2 more
openaire   +2 more sources

Total variation norm-based nonnegative matrix factorization for identifying discriminant representation of image patterns

Neurocomputing, 2008
The low-rank approximation technique of nonnegative matrix factorization (NMF) is emerging recently for finding parts-based structure of nonnegative data based on minimizing least-square error (L"2 norm). However, it has been observed that the proper norm for image processing is the total variation norm (TVN) other than the L"2 norm, and image ...
Taiping Zhang, Bin Fang 0001, Weining Liu, Yuan Yan Tang, Guanghui He, Jing Wen   +5 more
openaire   +1 more source

Hyperspectral Unmixing Using Weighted L_1/2 Sparse Total Variation Regularized and Volume Prior Constrained Nonnegative Matrix Factorization

IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019
Nonnegative matrix factorization (NMF) has been widely used in hyperspectral unmixing (HU) in recent years since it can simultaneously estimate endmember and abundance matrices. However, most existing NMF unmixing methods only impose geometric or statistical unilateral prior on endmember or abundance matrix, meanwhile ignore the synergistic effect of ...
Kewen Qu, Wenxing Bao, Xiangfei Shen
openaire   +2 more sources

Reweighted sparsity regularized deep nonnegative matrix factorization with total variation toward hyperspectral unmixing

National Remote Sensing Bulletin, 2020
ZHU Wei, WANG Xue, HUANG Yan, DU Peijun, TAN Kun   +4 more
openaire   +1 more source

On the Total Nonnegativity of the Hurwitz Matrix

SIAM Journal on Applied Mathematics, 1970
openaire   +1 more source

Jordan structures of irreducible totally nonnegative matrices with a prescribed sequence of the first p-indices

Revista De La Real Academia De Ciencias Exactas, Fisicas Y Naturales - Serie A: Matematicas, 2022
Ana Maria Urbano, Rafael Canto, Begoña Canto   +2 more
exaly  

Accurate Eigenvalues and SVDs of Totally Nonnegative Matrices

SIAM Journal on Matrix Analysis and Applications, 2005
Plamen Koev
exaly  

Accurate Computations with Totally Nonnegative Matrices

SIAM Journal on Matrix Analysis and Applications, 2007
Plamen Koev
exaly  

Spectral Structures of Irreducible Totally Nonnegative Matrices

SIAM Journal on Matrix Analysis and Applications, 2000
Shaun M Fallat
exaly