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2019 IEEE Transactions on Geoscience and Remote Sensing  
Benediktsson 5085 Simultaneous Reconstruction and Anomaly Detection of Subsampled Hyperspectral Images Using l (1/2) Regularized Joint Sparse and Low-Rank Recovery .....................................  ...  Yin 4938 Effects of Compression on Remote Sensing Image Classification Based on Fractal Analysis ............................. ..........................................................................  ... 
doi:10.1109/tgrs.2019.2923179 fatcat:nfaahnqzcvft5ezz36a6nyy2ri

2019 Index IEEE Transactions on Geoscience and Remote Sensing Vol. 57

2019 IEEE Transactions on Geoscience and Remote Sensing  
., and Drake, V.A., Insect Biological Parameter Estimation Based on the Invariant Target Parameters of the Scattering Matrix; TGRS Aug. 2019 6212-6225 Hu, C., see Zhang, M., TGRS Sept. 2019 6666-6674  ...  on Arbitrary Region of Interest; TGRS Oct. 2019 7995-8010 Hu, T., see Kang, Z., TGRS Jan. 2019 181-193 Hu, T., Wu, Y., Zheng, G., Zhang, D., Zhang, Y., and Li, Y., Tropical Cyclone Center  ...  Zhang, W., +, TGRS July 2019 4810-4822 Simultaneous Reconstruction and Anomaly Detection of Subsampled Hyperspectral Images Using I (1/2) Regularized Joint Sparse and Low-Rank Recovery.  ... 
doi:10.1109/tgrs.2020.2967201 fatcat:kpfxoidv5bgcfo36zfsnxe4aj4

Detection of Small Target Using Schatten 1/2 Quasi-Norm Regularization with Reweighted Sparse Enhancement in Complex Infrared Scenes

Fei Zhou, Yiquan Wu, Yimian Dai, Peng Wang
2019 Remote Sensing  
Finally, the small target detection task is reformulated as a problem of nonconvex low-rank matrix recovery with sparse reweighting.  ...  Extensive experimental results on several real infrared scene datasets validate the superiority of the proposed method over the state-of-the-arts with respect to background interference suppression and  ...  Acknowledgments: The authors would like to thank the editor and anonymous reviewers for their help comments and suggestions and thank Chengqiang Gao and Xiaoyang Wang providing images and the codes for  ... 
doi:10.3390/rs11172058 fatcat:346lahswwnc3zfwyy5t7yen3ia

Front Matter: Volume 10806

Xudong Jiang, Jenq-Neng Hwang
2018 Tenth International Conference on Digital Image Processing (ICDIP 2018)  
Utilization of CIDs allows articles to be fully citable as soon as they are published online, and connects the same identifier to all online and print versions of the publication.  ...  . ▪ The last two digits indicate publication order within the volume using a Base 36 numbering system employing both numerals and letters. These two-number sets start with 00, 01, 02, 03, 04,  ...  mass spectrometry database of microbes based on SVM [10806-239] 10806 5M Medical image fusion based on NSCT and sparse representation [10806-244] xiv Proc. of SPIE Vol. 10806 1080601-14 Deep  ... 
doi:10.1117/12.2510343 fatcat:maohjht2t5apneao4iivotwxey

Unmanned Ground Vehicle Navigation Using Aerial Ladar Data

Nicolas Vandapel, Raghavendra Rao Donamukkala, Martial Hebert
2006 The international journal of robotics research  
In this paper, we investigate the use of overhead high-resolution three-dimensional (3-D) data for enhancing the performances of an Unmanned Ground Vehicle (UGV) in vegetated terrains.  ...  Vegetation is filtered both in the ground data and in the aerial data in order to recover the load bearing surface.  ...  This work would not have been possible without the help of W. Klarquist and Jeremy Nett from PercepTEK.  ... 
doi:10.1177/0278364906061161 fatcat:n7fnreuzfratbgk3ditnsnszvy

Landslide inventory maps: New tools for an old problem

Fausto Guzzetti, Alessandro Cesare Mondini, Mauro Cardinali, Federica Fiorucci, Michele Santangelo, Kang-Tsung Chang
2012 Earth-Science Reviews  
Conventional methods for the production of landslide maps rely chiefly on the visual interpretation of stereoscopic aerial photography, aided by field surveys.  ...  New and emerging techniques based on satellite, airborne, and terrestrial remote sensing technologies, promise to facilitate the production of landslide maps, reducing the time and resources required for  ...  In most cases, detection and mapping of the landslides is based on the visual interpretation of 2D and 3D representations of the subaqueous terrain (Schwab et al., 1991; Hampton et al., 1996; Masson et  ... 
doi:10.1016/j.earscirev.2012.02.001 fatcat:6sg2izvefzgwbeoprv67avxnpe

2019 Index IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Vol. 12

2019 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
., and Lopez, J.F  ...  via Subspace-Based Nonlocal Low-Rank and Sparse Factorization.  ...  ., +, JSTARS April 2019 1134-1142 Kernel Low-Rank Representation Based on Local Similarity for Hyperspectral Image Classification.  ... 
doi:10.1109/jstars.2020.2973794 fatcat:sncrozq3fjg4bgjf4lnkslbz3u

2021 Index IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Vol. 14

2021 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination.  ...  The Subject Index contains entries describing the item under all appropriate subject headings, plus the first author's name, the publication abbreviation, month, and year, and inclusive pages.  ...  ., +, JSTARS 2021 7895-7910 Anomaly Detection for Hyperspectral Images Based on Improved Low-Rank and Sparse Representation and Joint Gaussian Mixture Distribution.  ... 
doi:10.1109/jstars.2022.3143012 fatcat:dnetkulbyvdyne7zxlblmek2qy

The Potential of Machine Learning for a More Responsible Sourcing of Critical Raw Materials

Pedram Ghamisi, Kasra Rafiezadeh Shahi, Puhong Duan, Behnood Rasti, Sandra Lorenz, Rene Booysen, Samuel Thiele, Isabel Cecilia Contreras Acosta, Moritz Kirsch, Richard Gloaguen
2021 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
of raw material extraction, classification, and process automatization.  ...  We first describe the main imagers and the acquired data types as well as the platforms on which they can be installed.  ...  Later on, sparse and low-rank representations showed considerable advantages compared with the sparse and redundant representations [36] - [38] .  ... 
doi:10.1109/jstars.2021.3108049 fatcat:dopyzl427rhmbi7nejpug7ahfq

Mitigation of Radio Frequency Interference in Synthetic Aperture Radar Data: Current Status and Future Trends

Mingliang Tao, Jia Su, Yan Huang, Ling Wang
2019 Remote Sensing  
Advantages and drawbacks of each approach are discussed in terms of their applicability. Discussion on the future trends are provided from the perspective of cognitive, integrated, and adaptive.  ...  From the view of spectrum allocation, possible terrestrial and spaceborne RFI sources to SAR system and their geometry are analyzed.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/rs11202438 fatcat:7mlqnrz725afnoja4sksnoladu

2014 Index IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Vol. 7

2014 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
., and Foerster, S  ...  ., +, JSTARS Dec. 2014 4653-4669 Pansharpening Based on Low-Rank and Sparse Decomposition.  ...  ., +, JSTARS July 2014 3117-3127 Pansharpening Based on Low-Rank and Sparse Decomposition.  ... 
doi:10.1109/jstars.2015.2397347 fatcat:ib3tjwsjsnd6ri6kkklq5ov37a

Meta-Analysis of Unmanned Aerial Vehicle (UAV) Imagery for Agro-Environmental Monitoring Using Machine Learning and Statistical Models

Roghieh Eskandari, Masoud Mahdianpari, Fariba Mohammadimanesh, Bahram Salehi, Brian Brisco, Saeid Homayouni
2020 Remote Sensing  
Unmanned Aerial Vehicle (UAV) imaging systems have recently gained significant attention from researchers and practitioners as a cost-effective means for agro-environmental applications.  ...  The meta-analysis revealed that 62% and 38% of the studies applied regression and classification models, respectively.  ...  The superiority of object-based approaches over pixel-based ones in terms of classification performance is proven in [110] .  ... 
doi:10.3390/rs12213511 fatcat:y6eoqjaxbbc4rafodjowrqwxwe

A Boosting SAR Image Despeckling Method Based on Non-Local Weighted Group Low-Rank Representation

Jing Fang, Shaohai Hu, Xiaole Ma
2018 Sensors  
Based on this, we use low-rank representation (LRR) to recover the noise-free group data matrix.  ...  In this paper, we propose a boosting synthetic aperture radar (SAR) image despeckling method based on non-local weighted group low-rank representation (WGLRR).  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/s18103448 pmid:30322174 pmcid:PMC6210930 fatcat:e3idmup56rcwxpcv2qlxsvrvc4

Sparsity-Driven Synthetic Aperture Radar Imaging: Reconstruction, autofocusing, moving targets, and compressed sensing

Mujdat Cetin, Ivana Stojanovic, Ozben Onhon, Kush Varshney, Sadegh Samadi, William Clem Karl, Alan S. Willsky
2014 IEEE Signal Processing Magazine  
Recent theoretical work on low-rank models shares many aspects of earlier work on sparsity and CS: low-rank matrix recovery problems are posed as optimization problems, relaxed forms of which, involving  ...  decomposition of some of the signals into sparse and low-rank components as well.  ...  set containing the largest % t column crosscorrelations . gij Based on this definition, ( ) H t% n measures the average cross-correlation value within the set of the t% most similar column pairs.  ... 
doi:10.1109/msp.2014.2312834 fatcat:47honwuywjgvnazjflqllmu7fm

Regional mapping of spekboom canopy cover using very high resolution aerial imagery

Dugal Harris, Jan Vlok, Adriaan van Niekerk
2018 Journal of Applied Remote Sensing  
Results confirmed that redundancy has a negative impact on commonly used ranking and greedy search (stepwise) feature selection methods.  ...  A set of 2228 aerial images covering the study area was subsequently acquired from Chief Directorate: National Geo-spatial Information (NGI).  ...  IMAGE CLASSIFICATION Image classification refers to the process of assigning objects into classes based on the information contained in the image.  ... 
doi:10.1117/1.jrs.12.046022 fatcat:zy5b5vazuzb3xezt2izq7s37wi
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