Convex Formulation for Multiband Image Classification With Superpixel-Based Spatial Regularization
暂无分享,去创建一个
Jun Li | Peijun Du | Yi Liu | José M. Bioucas-Dias | Antonio Plaza | Jun Yu Li | Filipe Condessa | A. Plaza | J. Bioucas-Dias | Peijun Du | Filipe Condessa | Yi Liu
[1] Jelena Kovacevic,et al. SegSALSA-STR: A convex formulation to supervised hyperspectral image segmentation using hidden fields and structure tensor regularization , 2015, 2015 7th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS).
[2] Antonio J. Plaza,et al. Semi-supervised hyperspectral image classification based on a Markov random field and sparse multinomial logistic regression , 2009, 2009 IEEE International Geoscience and Remote Sensing Symposium.
[3] Tony F. Chan,et al. Active contours without edges , 2001, IEEE Trans. Image Process..
[4] Daniel Cremers,et al. A Survey and Comparison of Discrete and Continuous Multi-label Optimization Approaches for the Potts Model , 2013, International Journal of Computer Vision.
[5] V. Jelen,et al. Mobility tracking by interactive graph-cut segmentation with Bi-elliptical shape prior , 2010, 2010 IEEE 8th International Symposium on Applied Machine Intelligence and Informatics (SAMI).
[6] Pascal Fua,et al. SLIC Superpixels Compared to State-of-the-Art Superpixel Methods , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[7] Vladimir Kolmogorov,et al. Convergent Tree-Reweighted Message Passing for Energy Minimization , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[8] Jon Atli Benediktsson,et al. Multiple Spectral–Spatial Classification Approach for Hyperspectral Data , 2010, IEEE Transactions on Geoscience and Remote Sensing.
[9] Daphne Koller,et al. Subproblem-Tree Calibration: A Unified Approach to Max-Product Message Passing , 2013, ICML.
[10] Jon Atli Benediktsson,et al. Spectral–Spatial Classification of Hyperspectral Imagery Based on Partitional Clustering Techniques , 2009, IEEE Transactions on Geoscience and Remote Sensing.
[11] Antonio J. Plaza,et al. A Discontinuity Preserving Relaxation Scheme for Spectral–Spatial Hyperspectral Image Classification , 2016, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[12] José M. Bioucas-Dias,et al. An Augmented Lagrangian Approach to the Constrained Optimization Formulation of Imaging Inverse Problems , 2009, IEEE Transactions on Image Processing.
[13] Ravi Bansal,et al. Segmentation of Dynamic N-D Data Sets via Graph Cuts Using Markov Models , 2001, MICCAI.
[14] Vladimir Kolmogorov,et al. Optimizing Binary MRFs via Extended Roof Duality , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.
[15] Jon Atli Benediktsson,et al. A spatial-spectral kernel-based approach for the classification of remote-sensing images , 2012, Pattern Recognit..
[16] Antonio J. Plaza,et al. Parallel and Distributed Dimensionality Reduction of Hyperspectral Data on Cloud Computing Architectures , 2016, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[17] D. Greig,et al. Exact Maximum A Posteriori Estimation for Binary Images , 1989 .
[18] Shuai Yang,et al. Superpixel-Based Classification Using K Distribution and Spatial Context for Polarimetric SAR Images , 2016, Remote. Sens..
[19] Daniel Cremers,et al. The Natural Vectorial Total Variation Which Arises from Geometric Measure Theory , 2012, SIAM J. Imaging Sci..
[20] Petros Maragos,et al. Convex Generalizations of Total Variation Based on the Structure Tensor with Applications to Inverse Problems , 2013, SSVM.
[21] Chunming Li,et al. Minimization of Region-Scalable Fitting Energy for Image Segmentation , 2008, IEEE Transactions on Image Processing.
[22] Daniel Cremers,et al. An Experimental Comparison of Discrete and Continuous Shape Optimization Methods , 2008, ECCV.
[23] Stephen P. Boyd,et al. Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers , 2011, Found. Trends Mach. Learn..
[24] Pushmeet Kohli,et al. Robust Higher Order Potentials for Enforcing Label Consistency , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[25] Donald Geman,et al. Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images , 1984 .
[26] Yu Jin Zhang,et al. A review of recent evaluation methods for image segmentation , 2001, Proceedings of the Sixth International Symposium on Signal Processing and its Applications (Cat.No.01EX467).
[27] Patrick L. Combettes,et al. Proximal Splitting Methods in Signal Processing , 2009, Fixed-Point Algorithms for Inverse Problems in Science and Engineering.
[28] L. Padma Suresh,et al. Image segmentation using seeded region growing , 2012, 2012 International Conference on Computing, Electronics and Electrical Technologies (ICCEET).
[29] Vijay K. Jain,et al. Markov random field for tumor detection in digital mammography , 1995, IEEE Trans. Medical Imaging.
[30] Marie-Pierre Jolly,et al. Interactive graph cuts for optimal boundary & region segmentation of objects in N-D images , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.
[31] Tomás Werner,et al. A Linear Programming Approach to Max-Sum Problem: A Review , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[32] Jon Atli Benediktsson,et al. Spectral–Spatial Classification of Hyperspectral Images With a Superpixel-Based Discriminative Sparse Model , 2015, IEEE Transactions on Geoscience and Remote Sensing.
[33] Jelena Kovacevic,et al. Alternating direction optimization for image segmentation using hidden Markov measure field models , 2014, Electronic Imaging.
[34] William M. Wells,et al. Simultaneous truth and performance level estimation (STAPLE): an algorithm for the validation of image segmentation , 2004, IEEE Transactions on Medical Imaging.
[35] José M. F. Moura,et al. Signal inpainting on graphs via total variation minimization , 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[36] Jelena Kovacevic,et al. Supervised hyperspectral image segmentation: A convex formulation using hidden fields , 2014, 2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS).
[37] Edgar Arce Santana,et al. Hidden Markov Measure Field Models for Image Segmentation , 2003, IEEE Trans. Pattern Anal. Mach. Intell..
[38] Gareth Funka-Lea,et al. Graph Cuts and Efficient N-D Image Segmentation , 2006, International Journal of Computer Vision.
[39] T. Chan,et al. Fast dual minimization of the vectorial total variation norm and applications to color image processing , 2008 .
[40] S. Thayammal,et al. A Review On Segmentation Based I mage Compression Techniques , 2013 .
[41] Daniel Cremers,et al. A convex relaxation approach for computing minimal partitions , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[42] Filipe Condessa. Robust Image Classification with Context and Rejection , 2016 .
[43] Jitendra Malik,et al. Scale-Space and Edge Detection Using Anisotropic Diffusion , 1990, IEEE Trans. Pattern Anal. Mach. Intell..
[44] Vladimir Kolmogorov,et al. Minimizing Nonsubmodular Functions with Graph Cuts-A Review , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[45] Tien Yin Wong,et al. Superpixel Classification Based Optic Disc and Optic Cup Segmentation for Glaucoma Screening , 2013, IEEE Transactions on Medical Imaging.
[46] Tommi S. Jaakkola,et al. Fixing Max-Product: Convergent Message Passing Algorithms for MAP LP-Relaxations , 2007, NIPS.
[47] Jiankun Hu,et al. Superpixel-Based Graphical Model for Remote Sensing Image Mapping , 2015, IEEE Transactions on Geoscience and Remote Sensing.
[48] Vladimir Kolmogorov,et al. An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision , 2004, IEEE Trans. Pattern Anal. Mach. Intell..
[49] Martin J. Wainwright,et al. On the Optimality of Tree-reweighted Max-product Message-passing , 2005, UAI.
[50] Antonio J. Plaza,et al. Joint Sparse Sub-Pixel Mapping Model with Endmember Variability for Remotely Sensed Imagery , 2016, Remote. Sens..
[51] Jan-Michael Frahm,et al. Fast Global Labeling for Real-Time Stereo Using Multiple Plane Sweeps , 2008, VMV.
[52] Jun Li,et al. GPU Parallel Implementation of Spatially Adaptive Hyperspectral Image Classification , 2018, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[53] Jon Atli Benediktsson,et al. Segmentation and classification of hyperspectral images using watershed transformation , 2010, Pattern Recognit..
[54] Antonio J. Plaza,et al. This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 1 Spectral–Spatial Classification of Hyperspectral Data Usi , 2022 .
[55] J. Chanussot,et al. Hyperspectral Remote Sensing Data Analysis and Future Challenges , 2013, IEEE Geoscience and Remote Sensing Magazine.
[56] Mário A. T. Figueiredo. Bayesian image segmentation using wavelet-based priors , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[57] Michele Volpi,et al. Semantic segmentation of urban scenes by learning local class interactions , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).