ℓ0-based sparse hyperspectral unmixing using spectral information and a multi-objectives formulation
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Zhenwei Shi | Bin Pan | Xia Xu | Zhenwei Shi | Bin Pan | Xia Xu
[1] Gaofeng Meng,et al. Spectral Unmixing via Data-Guided Sparsity , 2014, IEEE Transactions on Image Processing.
[2] Maoguo Gong,et al. A Multiobjective Cooperative Coevolutionary Algorithm for Hyperspectral Sparse Unmixing , 2017, IEEE Transactions on Evolutionary Computation.
[3] Ning Zhang,et al. Hyperspectral Image Classification Based on Nonlinear Spectral–Spatial Network , 2016, IEEE Geoscience and Remote Sensing Letters.
[4] Xin Yao,et al. On the approximation ability of evolutionary optimization with application to minimum set cover , 2010, Artif. Intell..
[5] Richard G. Baraniuk,et al. Sparsity and Structure in Hyperspectral Imaging : Sensing, Reconstruction, and Target Detection , 2014, IEEE Signal Processing Magazine.
[6] Kalyanmoy Deb,et al. An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point Based Nondominated Sorting Approach, Part II: Handling Constraints and Extending to an Adaptive Approach , 2014, IEEE Transactions on Evolutionary Computation.
[7] R. K. Ursem. Multi-objective Optimization using Evolutionary Algorithms , 2009 .
[8] Derrick Wing Kwan Ng,et al. Multi-Objective Optimization for Robust Power Efficient and Secure Full-Duplex Wireless Communication Systems , 2015, IEEE Transactions on Wireless Communications.
[9] Antonio J. Plaza,et al. Sparse Unmixing of Hyperspectral Data , 2011, IEEE Transactions on Geoscience and Remote Sensing.
[10] K. C. Ho,et al. Endmember Variability in Hyperspectral Analysis: Addressing Spectral Variability During Spectral Unmixing , 2014, IEEE Signal Processing Magazine.
[11] Qi Wang,et al. Salient Band Selection for Hyperspectral Image Classification via Manifold Ranking , 2016, IEEE Transactions on Neural Networks and Learning Systems.
[12] Yang Yu,et al. On Constrained Boolean Pareto Optimization , 2015, IJCAI.
[13] Yicong Zhou,et al. Learning Hierarchical Spectral–Spatial Features for Hyperspectral Image Classification , 2016, IEEE Transactions on Cybernetics.
[14] Yang Yu,et al. Parallel Pareto Optimization for Subset Selection , 2016, IJCAI.
[15] Liangpei Zhang,et al. Adaptive Spatial Regularization Sparse Unmixing Strategy Based on Joint MAP for Hyperspectral Remote Sensing Imagery , 2016, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[16] Ying Wang,et al. Structured Sparse Method for Hyperspectral Unmixing , 2014, ArXiv.
[17] Qingfu Zhang,et al. MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition , 2007, IEEE Transactions on Evolutionary Computation.
[18] José M. Bioucas-Dias,et al. Semiblind Hyperspectral Unmixing in the Presence of Spectral Library Mismatches , 2015, IEEE Transactions on Geoscience and Remote Sensing.
[19] Antonio J. Plaza,et al. Total Variation Spatial Regularization for Sparse Hyperspectral Unmixing , 2012, IEEE Transactions on Geoscience and Remote Sensing.
[20] Xin Yao,et al. An Evolutionary Multiobjective Approach to Sparse Reconstruction , 2014, IEEE Transactions on Evolutionary Computation.
[21] Zexuan Zhu,et al. Computational intelligence in optical remote sensing image processing , 2018, Appl. Soft Comput..
[22] Lin Zhao,et al. Blind spectral unmixing based on sparse component analysis for hyperspectral remote sensing imagery , 2016 .
[23] José M. Bioucas-Dias,et al. Alternating direction algorithms for constrained sparse regression: Application to hyperspectral unmixing , 2010, 2010 2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing.
[24] Thomas Cudahy,et al. Mapping white micas and their absorption wavelengths using hyperspectral band ratios , 2006 .
[25] Xin Yao,et al. A Survey on Evolutionary Computation Approaches to Feature Selection , 2016, IEEE Transactions on Evolutionary Computation.
[26] Zhiguo Jiang,et al. Subspace Matching Pursuit for Sparse Unmixing of Hyperspectral Data , 2014, IEEE Transactions on Geoscience and Remote Sensing.
[27] Zhenwei Shi,et al. Multi-objective based spectral unmixing for hyperspectral images , 2017 .
[28] Antonio J. Plaza,et al. Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches , 2012, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[29] Ruyi Feng,et al. Adaptive non-local Euclidean medians sparse unmixing for hyperspectral imagery , 2014 .
[30] Antonio J. Plaza,et al. A Signal Processing Perspective on Hyperspectral Unmixing: Insights from Remote Sensing , 2014, IEEE Signal Processing Magazine.
[31] Kaisa Miettinen,et al. Nonlinear multiobjective optimization , 1998, International series in operations research and management science.
[32] Antonio J. Plaza,et al. Collaborative Sparse Regression for Hyperspectral Unmixing , 2014, IEEE Transactions on Geoscience and Remote Sensing.
[33] Qingfu Zhang,et al. Multiobjective evolutionary algorithms: A survey of the state of the art , 2011, Swarm Evol. Comput..
[34] John F. Mustard,et al. Spectral unmixing , 2002, IEEE Signal Process. Mag..
[35] Xia Xu,et al. R-VCANet: A New Deep-Learning-Based Hyperspectral Image Classification Method , 2017, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[36] Ridong Zhang,et al. Data-Driven Modeling Using Improved Multi-Objective Optimization Based Neural Network for Coke Furnace System , 2017, IEEE Transactions on Industrial Electronics.
[37] Yang Yu,et al. Subset Selection by Pareto Optimization , 2015, NIPS.
[38] Paul D. Gader,et al. A Review of Nonlinear Hyperspectral Unmixing Methods , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[39] Le Wang,et al. Incorporating spatial information in spectral unmixing: A review , 2014 .
[40] Da He,et al. Multiobjective Subpixel Land-Cover Mapping , 2018, IEEE Transactions on Geoscience and Remote Sensing.
[41] Zhenwei Shi,et al. MugNet: Deep learning for hyperspectral image classification using limited samples , 2017, ISPRS Journal of Photogrammetry and Remote Sensing.
[42] Liangpei Zhang,et al. Spatial Group Sparsity Regularized Nonnegative Matrix Factorization for Hyperspectral Unmixing , 2017, IEEE Transactions on Geoscience and Remote Sensing.
[43] Jun Zhou,et al. Hyperspectral Unmixing via $L_{1/2}$ Sparsity-Constrained Nonnegative Matrix Factorization , 2011, IEEE Transactions on Geoscience and Remote Sensing.
[44] José M. Bioucas-Dias,et al. Hyperspectral Subspace Identification , 2008, IEEE Transactions on Geoscience and Remote Sensing.
[45] Antonio J. Plaza,et al. MUSIC-CSR: Hyperspectral Unmixing via Multiple Signal Classification and Collaborative Sparse Regression , 2014, IEEE Transactions on Geoscience and Remote Sensing.
[46] Ying Wu,et al. Regularized Simultaneous Forward–Backward Greedy Algorithm for Sparse Unmixing of Hyperspectral Data , 2014, IEEE Transactions on Geoscience and Remote Sensing.
[47] Jieping Ye,et al. A General Iterative Shrinkage and Thresholding Algorithm for Non-convex Regularized Optimization Problems , 2013, ICML.
[48] Liangpei Zhang,et al. Adaptive Multiobjective Memetic Fuzzy Clustering Algorithm for Remote Sensing Imagery , 2015, IEEE Transactions on Geoscience and Remote Sensing.
[49] Kalyanmoy Deb,et al. An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point-Based Nondominated Sorting Approach, Part I: Solving Problems With Box Constraints , 2014, IEEE Transactions on Evolutionary Computation.
[50] Chein-I Chang,et al. Estimation of number of spectrally distinct signal sources in hyperspectral imagery , 2004, IEEE Transactions on Geoscience and Remote Sensing.