[PDF] Top 20 Exploration of Unmixing and Classification of Hyperspectral Imagery
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Exploration of Unmixing and Classification of Hyperspectral Imagery
... of Hyperspectral sensors mixed pixel ...These hyperspectral images provide good resolution, and the range of spectra will give the ability to identify the chemical species present in the atmosphere of Mars ... See full document
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Toward a Sparse Bayesian Markov Random Field Approach to Hyperspectral Unmixing and Classification
... In the proposed model, β in (5) can be considered as the inverse temperature T = 1/β. Smaller β will present a weaker spatial prior and will therefore tend to result in “noisier” maps, whilst larger values give stronger ... See full document
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LiDAR-driven spatial regularization for hyperspectral unmixing
... Terms— Hyperspectral imagery, spectral unmix- ing, edge, lidar, classification ...Spectral unmixing aims at deconvolving the spectral mixtures into a collection of refer- ence spectra, known ... See full document
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Efficient Nonlinear Dimensionality Reduction for Pixel-wise Classification of Hyperspectral Imagery
... used for denoising and the other is used to estimate the endmembers. To sum up, different kinds of autoencoders have been widely used in a variety of HSI applications, including classification, unmixing, ... See full document
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Matrix Cofactorization for Joint Unmixing and Classification of Hyperspectral Images
... spectral unmixing, cofac- torization, hyperspectral ...particular classification algorithms received a lot of attention from the scientific ...supervised classification framework, these ... See full document
6
Matrix-Vector Nonnegative Tensor Factorization for Blind Unmixing of Hyperspectral Imagery
... III. M ATRIX -V ECTOR N ONNEGATIVE T ENSOR F ACTORIZATION BASED U NMIXING MODEL In the last section, we have built a link between matrix- vector tensor factorization and linear spectral mixture model on their form of ... See full document
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A Bayesian model for joint unmixing and robust classification of hyperspectral image
... Supervised classification and spectral unmixing are two methods to extract information from hyperspectral ...the classification. Finally, the classification exploits a set of possibly ... See full document
6
A Bayesian model for joint unmixing, clustering and classification of hyperspectral data
... Séminaire des doctorants – April 28th, 2017.. Context Model Experiments Conclusions and perspectives Context Hyperspectral imaging Objective Model Spectral unmixing Clustering Classifica[r] ... See full document
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Hyperspectral Clustering and Unmixing of Satellite Imagery for the Study of Complex Society State Formation
... Hyperion imagery for future seasonal ...that imagery can be made internet ...sharing imagery extremely efficient and convenient, it solves the issue of researchers having to download (or ship) large ... See full document
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Hyperspectral Clustering and Unmixing of Satellite Imagery for the Study of Complex Society State Formation
... the imagery was developed based on the functionality of the IDL programming language along with its ENVI ...(L1R) imagery does not suffer from this issue; however, geo-referencing and application of a ... See full document
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Semi-supervised linear spectral unmixing using a hierarchical Bayesian model for hyperspectral imagery
... spectral unmixing to be effective, three key issues must be ...spectral unmixing is devoted to the third issue, the first and second issues have been largely ignored or avoided by assuming availability of ... See full document
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Unmixing-Based Fusion of Hyperspatial and Hyperspectral Airborne Imagery for Early Detection of Vegetation Stress
... http://dx.doi.org/10.1109/JSTARS.2014.2330352 http://hdl.handle.net/10251/60797 Institute of Electrical and Electronics Engineers (IEEE) Delalieux, S.; Zarco-Tejada, PJ.; Tits, L.; Jiménez Bello, MA.; Intrigliolo Molina, ... See full document
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Supervised nonlinear spectral unmixing using a post-nonlinear mixing model for hyperspectral imagery
... The first real image considered in this section is composed of spectral bands and was acquired in 1997 by the airborne visible infrared imaging spectrometer (AVIRIS) over the Cuprite mining site in Nevada. A subimage of ... See full document
10
Classification of high dimensional and imbalanced hyperspectral imagery data
... In this paper, some well-known strategies to cope with class imbalance are in- vestigated for the classification of hyperspectral imagery acquired by the Airborne Visible/Infrared Imaging ... See full document
8
The classification of hill country vegetation from hyperspectral imagery
... sensed hyperspectral data provides the possibility to categorise and quantify the farm landscape in great detail, supplementing local expert knowledge and adding confidence to ...of hyperspectral aerial ... See full document
10
Classification of Herbaceous Vegetation Using Airborne Hyperspectral Imagery
... Table 4. Confusion matrix of SVM classification using 9 MNF-transformed bands with 30 training pixels. Identical groups are represented by the same color (cyan—dry steppic grasslands; gray—open alkali grasslands; ... See full document
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Exploration of Planetary Hyperspectral Images with Unsupervised Spectral Unmixing: A Case Study of Planet Mars
... spectral unmixing methods for the exploration of large datasets of planetary hyperspectral ...of unmixing to the intrinsic spectral variability of the species in the image and to intimate ... See full document
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Spatial analysis for colon biopsy classification from hyperspectral imagery
... that metrics based on the responses of receptive field operators model the orientational selec- tivity of neurons. These operators are found in the early visual pathway and are capable of discriminating between images of ... See full document
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Collaborative Representation and Sparsity are Both Indispensable for Hyperspectral Imagery Classification
... HSI classification, and neither can work effectively without each ...HSI classification is a typical high dimensional problem with small sample size, leading to an under-completed ...wrong ... See full document
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Classification of hyperspectral imagery with neural networks: comparison to conventional tools
... of hyperspectral imagery is of great importance in remote ...for classification of hyperspectral data because the complexity of such data challenges the limitations of many conventional ...of ... See full document
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