Literatura académica sobre el tema "Sparse hyperspectral unmixing"
Crea una cita precisa en los estilos APA, MLA, Chicago, Harvard y otros
Consulte las listas temáticas de artículos, libros, tesis, actas de conferencias y otras fuentes académicas sobre el tema "Sparse hyperspectral unmixing".
Junto a cada fuente en la lista de referencias hay un botón "Agregar a la bibliografía". Pulsa este botón, y generaremos automáticamente la referencia bibliográfica para la obra elegida en el estilo de cita que necesites: APA, MLA, Harvard, Vancouver, Chicago, etc.
También puede descargar el texto completo de la publicación académica en formato pdf y leer en línea su resumen siempre que esté disponible en los metadatos.
Artículos de revistas sobre el tema "Sparse hyperspectral unmixing"
Deng, Chengzhi, Yaning Zhang, Shengqian Wang, Shaoquan Zhang, Wei Tian, Zhaoming Wu y Saifeng Hu. "Approximate Sparse Regularized Hyperspectral Unmixing". Mathematical Problems in Engineering 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/947453.
Texto completoDeng, Chengzhi, Yonggang Chen, Shaoquan Zhang, Fan Li, Pengfei Lai, Dingli Su, Min Hu y Shengqian Wang. "Robust Dual Spatial Weighted Sparse Unmixing for Remotely Sensed Hyperspectral Imagery". Remote Sensing 15, n.º 16 (16 de agosto de 2023): 4056. http://dx.doi.org/10.3390/rs15164056.
Texto completoZhang, Shuaiyang, Wenshen Hua, Gang Li, Jie Liu, Fuyu Huang y Qianghui Wang. "Double Regression-Based Sparse Unmixing for Hyperspectral Images". Journal of Sensors 2021 (3 de septiembre de 2021): 1–14. http://dx.doi.org/10.1155/2021/5575155.
Texto completoFeng, Ruyi, Lizhe Wang y Yanfei Zhong. "Joint Local Block Grouping with Noise-Adjusted Principal Component Analysis for Hyperspectral Remote-Sensing Imagery Sparse Unmixing". Remote Sensing 11, n.º 10 (23 de mayo de 2019): 1223. http://dx.doi.org/10.3390/rs11101223.
Texto completoLi, Yalan, Yixuan Li, Wenwu Xie, Qian Du, Jing Yuan, Lin Li y Chen Qi. "Adaptive multiscale sparse unmixing for hyperspectral remote sensing image". Computer Science and Information Systems, n.º 00 (2023): 9. http://dx.doi.org/10.2298/csis220828009l.
Texto completoFeng, Dan, Mingyang Zhang y Shanfeng Wang. "Multipopulation Particle Swarm Optimization for Evolutionary Multitasking Sparse Unmixing". Electronics 10, n.º 23 (5 de diciembre de 2021): 3034. http://dx.doi.org/10.3390/electronics10233034.
Texto completoIordache, Marian-Daniel, José M. Bioucas-Dias y Antonio Plaza. "Sparse Unmixing of Hyperspectral Data". IEEE Transactions on Geoscience and Remote Sensing 49, n.º 6 (junio de 2011): 2014–39. http://dx.doi.org/10.1109/tgrs.2010.2098413.
Texto completoSigurdsson, Jakob, Magnus O. Ulfarsson, Johannes R. Sveinsson y Jose M. Bioucas-Dias. "Sparse Distributed Multitemporal Hyperspectral Unmixing". IEEE Transactions on Geoscience and Remote Sensing 55, n.º 11 (noviembre de 2017): 6069–84. http://dx.doi.org/10.1109/tgrs.2017.2720539.
Texto completoTong, Lei, Jing Yu, Chuangbai Xiao y Bin Qian. "Hyperspectral unmixing via deep matrix factorization". International Journal of Wavelets, Multiresolution and Information Processing 15, n.º 06 (noviembre de 2017): 1750058. http://dx.doi.org/10.1142/s0219691317500588.
Texto completoZhao, Genping, Fei Li, Xiuwei Zhang, Kati Laakso y Jonathan Cheung-Wai Chan. "Archetypal Analysis and Structured Sparse Representation for Hyperspectral Anomaly Detection". Remote Sensing 13, n.º 20 (13 de octubre de 2021): 4102. http://dx.doi.org/10.3390/rs13204102.
Texto completoTesis sobre el tema "Sparse hyperspectral unmixing"
Vila, Jeremy P. "Empirical-Bayes Approaches to Recovery of Structured Sparse Signals via Approximate Message Passing". The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1429191048.
Texto completoWei, Qi. "Bayesian fusion of multi-band images : A powerful tool for super-resolution". Phd thesis, Toulouse, INPT, 2015. http://oatao.univ-toulouse.fr/14398/1/wei.pdf.
Texto completoBieniarz, Jakub. "Sparse Methods for Hyperspectral Unmixing and Image Fusion". Doctoral thesis, 2016. https://repositorium.ub.uni-osnabrueck.de/handle/urn:nbn:de:gbv:700-2016030214286.
Texto completoAhmad, Touseef. "Augmenting Hyperspectral Image Unmixing Models Using Spatial Correlation, Spectral Variability, And Sparsity". Thesis, 2022. https://etd.iisc.ac.in/handle/2005/6081.
Texto completoNicolae, Aurel. "A comparative analysis of classic Geometrical methods and sparse regression methods for linearly unmixing hyperspectral image data". Thesis, 2019. https://hdl.handle.net/10539/29542.
Texto completoThis research report presents an across-the-board comparative analysis on algorithms for linearly unmixing hyperspectral image data cubes. Convex geometry based endmember extraction algorithms (EEAs) such as the pixel purity index (PPI) algorithm and N-FINDR have been commonly used to derive the material spectral signatures called endmembers from the hyperspectral images. The estimation of their corresponding fractional abundances is done by solving the related inverse problem in a least squares sense. Semi-supervised sparse regression algorithms such as orthogonal matching pursuit (OMP) and sparse unmixing algorithm via variable splitting and augmented Lagrangian (SUnSAL) bypass the endmember extraction process by employing widely available spectral libraries a priori, automatically returning the fractional abundances and sparsity estimates. The main contribution of this work is to serve as a rich resource on hyperspectral image unmixing, providing end-to-end evaluation of a wide variety of algorithms using di erent arti cial data sets.
XN2020
Capítulos de libros sobre el tema "Sparse hyperspectral unmixing"
Zhang, Shaoquan, Yuanchao Su, Xiang Xu, Jun Li, Chengzhi Deng y Antonio Plaza. "Recent Advances in Hyperspectral Unmixing Using Sparse Techniques and Deep Learning". En Hyperspectral Image Analysis, 377–405. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-38617-7_13.
Texto completoWu, Feiyang, Yuhui Zheng y Le Sun. "Sparse Unmixing for Hyperspectral Image with Nonlocal Low-Rank Prior". En Intelligence Science and Big Data Engineering. Visual Data Engineering, 506–16. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-36189-1_42.
Texto completoMarques, Ion y Manuel Graña. "Hybrid Sparse Linear and Lattice Method for Hyperspectral Image Unmixing". En Lecture Notes in Computer Science, 266–73. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07617-1_24.
Texto completoLiu, Jing, You Zhang, Xiao-die Yang y Yi Liu. "Hyperspectral Remote Sensing Images Unmixing Based on Sparse Concept Coding". En Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery, 823–30. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70665-4_89.
Texto completoZenati, Tarek, Bruno Figliuzzi y Shu Hui Ham. "Surface Oxide Detection and Characterization Using Sparse Unmixing on Hyperspectral Images". En Lecture Notes in Computer Science, 291–302. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-13321-3_26.
Texto completoEsmaeili Salehani, Yaser y Mohamed Cheriet. "Non-dictionary Aided Sparse Unmixing of Hyperspectral Images via Weighted Nonnegative Matrix Factorization". En Lecture Notes in Computer Science, 596–604. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-59876-5_66.
Texto completoChen, Mengyue, Fanqiang Kong, Shunmin Zhao y Keyao Wen. "Hyperspectral Unmixing Method Based on the Non-convex Sparse and Spatial Correlation Constraints". En Lecture Notes in Electrical Engineering, 441–46. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-8411-4_61.
Texto completoLi, Denggang, Shutao Li y Huali Li. "Hyperspectral Image Unmixing Based on Sparse and Minimum Volume Constrained Nonnegative Matrix Factorization". En Communications in Computer and Information Science, 44–52. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-45643-9_5.
Texto completoActas de conferencias sobre el tema "Sparse hyperspectral unmixing"
Sigurdsson, Jakob, Magnus O. Ulfarsson, Johannes R. Sveinsson y Jose M. Bioucas-Dias. "Sparse distributed hyperspectral unmixing". En IGARSS 2016 - 2016 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2016. http://dx.doi.org/10.1109/igarss.2016.7730824.
Texto completoIordache, Marian-Daniel, Jose Bioucas-Dias y Antonio Plaza. "Unmixing sparse hyperspectral mixtures". En 2009 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2009). IEEE, 2009. http://dx.doi.org/10.1109/igarss.2009.5417368.
Texto completoAggarwal, Hemant Kumar y Angshul Majumdar. "Sparse filtering based hyperspectral unmixing". En 2016 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS). IEEE, 2016. http://dx.doi.org/10.1109/whispers.2016.8071765.
Texto completoIordache, Marian-Daniel, Jose M. Bioucas-Dias y Antonio Plaza. "Collaborative sparse unmixing of hyperspectral data". En IGARSS 2012 - 2012 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2012. http://dx.doi.org/10.1109/igarss.2012.6351900.
Texto completoRodriguez Alves, Jose M., Jose M. P. Nascimento, Jose M. Bioucas-Dias, Antonio Plaza y Vitor Silva. "Parallel sparse unmixing of hyperspectral data". En IGARSS 2013 - 2013 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2013. http://dx.doi.org/10.1109/igarss.2013.6723057.
Texto completoIordache, Marian-Daniel, Antonio Plaza y Jose Bioucas-Dias. "Recent developments in sparse hyperspectral unmixing". En IGARSS 2010 - 2010 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2010. http://dx.doi.org/10.1109/igarss.2010.5653075.
Texto completoMa, Yong, Chang Li y Jiayi Ma. "Robust sparse unmixing of hyperspectral data". En IGARSS 2016 - 2016 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2016. http://dx.doi.org/10.1109/igarss.2016.7730618.
Texto completoSigurdsson, Jakob, Magnus O. Ulfarsson y Johannes R. Sveinsson. "Sparse and low rank hyperspectral unmixing". En 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). IEEE, 2017. http://dx.doi.org/10.1109/igarss.2017.8126936.
Texto completoChen, Yonggang, Chengzhi Deng, Shaoquan Zhang, Fan Li, Ningyuan Zhang y Shengqian Wang. "Dual Spatial Weighted Sparse Hyperspectral Unmixing". En IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2022. http://dx.doi.org/10.1109/igarss46834.2022.9883616.
Texto completoFang, Bei, Ying Li, Peng Zhang y Bendu Bai. "Kernel sparse NMF for hyperspectral unmixing". En 2014 IEEE International Conference on Orange Technologies (ICOT). IEEE, 2014. http://dx.doi.org/10.1109/icot.2014.6954672.
Texto completoInformes sobre el tema "Sparse hyperspectral unmixing"
Moeller, Michael, Ernie Esser, Stanley Osher, Guillermo Sapiro y Jack Xin. A Convex Model for Matrix Factorization and Dimensionality Reduction on Physical Space and Its Application to Blind Hyperspectral Unmixing. Fort Belvoir, VA: Defense Technical Information Center, octubre de 2010. http://dx.doi.org/10.21236/ada540658.
Texto completo