A real-time FPGA accelerated stream processing for hyperspectral image classification

AbstractRealizing real-time classification of hyperspectral imagery has attracted researchers across various scientific and engineering disciplines. Several time-critical applications of high-resol...

[1]  Inés del Campo,et al.  ELM-based hyperspectral imagery processor for onboard real-time classification , 2016, 2016 Conference on Design and Architectures for Signal and Image Processing (DASIP).

[2]  Hamid Saeed Khan,et al.  Modern Trends in Hyperspectral Image Analysis: A Review , 2018, IEEE Access.

[3]  Chih-Jen Lin,et al.  LIBSVM: A library for support vector machines , 2011, TIST.

[4]  A. Thorpe.  Mapping methane concentrations from a controlled release experiment using the next generation Airborne Visible/Infrared Imaging Spectrometer (AVIRISng) , 2014 .

[5]  Jun Li,et al.  Advanced Spectral Classifiers for Hyperspectral Images: A review , 2017, IEEE Geoscience and Remote Sensing Magazine.

[6]  Sildomar T. Monteiro,et al.  Evaluating Classification Techniques for Mapping Vertical Geology Using Field-Based Hyperspectral Sensors , 2012, IEEE Transactions on Geoscience and Remote Sensing.

[7]  Ning Ma,et al.  A Scalable Dataflow Accelerator for Real Time Onboard Hyperspectral Image Classification , 2016, ARC.

[8]  Yanjie Wang,et al.  Estimation of Winter Wheat Above-Ground Biomass Using Unmanned Aerial Vehicle-Based Snapshot Hyperspectral Sensor and Crop Height Improved Models , 2017, Remote. Sens..

[9]  Russell Tessier,et al.  Reconfigurable Computing Architectures , 2015, Proceedings of the IEEE.

[10]  Antonio J. Plaza,et al.  FPGA Implementation of Abundance Estimation for Spectral Unmixing of Hyperspectral Data Using the Image Space Reconstruction Algorithm , 2012, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[11]  Simon Bennertz,et al.  Specim IQ: Evaluation of a New, Miniaturized Handheld Hyperspectral Camera and Its Application for Plant Phenotyping and Disease Detection , 2018, Sensors.

[12]  Antonio J. Plaza,et al.  GPU Implementation of Composite Kernels for Hyperspectral Image Classification , 2015, IEEE Geoscience and Remote Sensing Letters.

[13]  Daniel Mozos,et al.  FPGA implementation of the principal component analysis algorithm for dimensionality reduction of hyperspectral images , 2019, Journal of Real-Time Image Processing.

[14]  Qian Du,et al.  Fast real-time onboard processing of hyperspectral imagery for detection and classification , 2009, Journal of Real-Time Image Processing.

[15]  Alexander F. H. Goetz,et al.  Three decades of hyperspectral remote sensing of the Earth: a personal view. , 2009 .

[16]  Tom Feist,et al.  Vivado Design Suite , 2012 .

[17]  Christos-Savvas Bouganis,et al.  Novel Cascade FPGA Accelerator for Support Vector Machines Classification , 2012, IEEE Transactions on Neural Networks and Learning Systems.

[18]  Chein-I Chang,et al.  Real-time processing algorithms for target detection and classification in hyperspectral imagery , 2001, IEEE Trans. Geosci. Remote. Sens..

[19]  Colm P. O'Donnell,et al.  Hyperspectral imaging – an emerging process analytical tool for food quality and safety control , 2007 .

[20]  Antonio J. Plaza,et al.  Dual-Mode FPGA Implementation of Target and Anomaly Detection Algorithms for Real-Time Hyperspectral Imaging , 2015, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[21]  Luis Alonso,et al.  Robust support vector method for hyperspectral data classification and knowledge discovery , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[22]  Lei Zhang,et al.  System generator model-based FPGA design optimization and hardware co-simulation for Lorenz chaotic generator , 2017, 2017 2nd Asia-Pacific Conference on Intelligent Robot Systems (ACIRS).

[23]  S. J. Sutley,et al.  Imaging spectroscopy: Earth and planetary remote sensing with the USGS Tetracorder and expert systems , 2003 .

[24]  Gustavo Marrero Callicó,et al.  SVM-based real-time hyperspectral image classifier on a manycore architecture , 2017, J. Syst. Archit..

[25]  Antonio J. Plaza,et al.  The Promise of Reconfigurable Computing for Hyperspectral Imaging Onboard Systems: A Review and Trends , 2013, Proceedings of the IEEE.

[26]  Lalit Kumar,et al.  Mapping Coastal Vegetation Using an Expert System and Hyperspectral Imagery , 2004 .

[27]  James Theiler,et al.  Algorithmic transformations in the implementation of K- means clustering on reconfigurable hardware , 2001, FPGA '01.