hyperspectral image (HSI) classification
A Novel Method for Remotely Sensed Hyperspectral Image Classification Based on Convolutional Neural Network
... The Hyperspectral Images (HSI) acquired by remote sensors are characterized by hundreds of contiguous channels with high spectral ...resolution. Hyperspectral image classification is the ...
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Spatial and Spectral Nonparametric Linear Feature Extraction Method for Hyperspectral Image Classification
... the classification speed, particularly when the training sample size is small, namely the small sample size (SSS) ...sensed hyperspectral images (HSIs) are often with hundreds of measured features (bands) ...
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Hyperspectral Image Classification Based on Hierarchical SVM Algorithm for Improving Overall Accuracy
... tral image classification. Hyperspectral image classification accuracy depends on the number of classes, training samples and features space ...The classification performance ...
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Uncertainty assessment of hyperspectral image classification: Deep learning vs random forest
... of classification accuracy, which can be used to locate and segregate unreliable pixel-level class allocations from reliable ...of classification approaches: unsupervised schemes using no training dataset ...
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Hyperspectral Image Classification using Softcomputing Techniques: A Review
... The hyperspectral classification falls into two major categories such as spectral classification and the spatial ...spectral classification, the reflectance values of the pixels at different ...
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Hyperspectral Image Classification For Based BEMD Multivariate Gray Module
... of Hyperspectral Image Classification Thus, hyperspectral imaging is concerned with the measurement, processing and analysis of spectra acquired from a given scene at a short, medium or long ...
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Spectral-spatial Feature Extraction for Hyperspectral Image Classification
... for hyperspectral images, the random sampling is usually undertaken on the same ...the image and the testing samples will locate adjacent to ...supervised hyperspectral image ...
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Hyperspectral Image Classification using Genetic Algorithm after Visualization using Image Fusion
... presents hyperspectral image classification using genetic algorithm after visualization using image fusion ...technique. Hyperspectral remote sensors collect image data for a ...
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A hyperspectral image classification algorithm based on atrous convolution
... HSI classification. First, the single-pixel classification of HSI learns the whole spectral information of each pixel, which not only solves the prob- lem of large computational complexity of ...
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Cone-based joint sparse modelling for hyperspectral image classification
... Joint sparse model (JSM) is being extensively investigated on hyperspectral images (HSIs) and has achieved promising performance for classification. In JSM, it is assumed that neighbouring ...
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Hybrid Subspace Detection based on Spectral and Spatial Information for Effective Hyperspectral Image Classification
... If the spatial size S is very large, the calculation of covariance matrix is difficult using PCA due to memory management issue [7]. Furthermore, PCA be unsuccessful to catch the individual contribution of each of the F ...
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Extreme sparse multinomial logistic regression : a fast and robust framework for hyperspectral image classification
... For efficiency, the input weights and the bias between the input layer and the hidden layer of the ELM are randomly generated. It has been proved to be a fast and good data representation method [30–32]. In fact, besides ...
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Infinite Latent Feature Selection Technique for Hyperspectral Image Classification
... In that paper, the Gaussian Mixture Model (GMM) was implemented to select important features before being processed in the forward feature selection. The results of this study are compared with the feature selection ...
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Hyperspectral image classification with SVM and guided filter
... of classification, recent studies have suggested incorporating spatial information into a spectral-based classifier [10], which is called the spectral-spatial HSI ...HSI classification. Various types of ...
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Robust joint sparsity model for hyperspectral image classification
... [14–18]. It assumes that each test sample can be sparsely rep- resented as a linear combination of atoms from a dictionary, which is constructed or learned from training samples [14]. Chen et al. [14] first applied the ...
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Hyperspectral image classification via contextual deep learning
... Pixel-wise classification methods process each pixel independently without considering the spatial informa- tion, but spatial contextual information of HSI is as impor- tant as the spectral information ...of ...
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Combined Features based Spatial Composite Kernel Formation for Hyperspectral Image Classification
... From the literature, it is evident that the care must be shown towards the feature extraction and classifier selection. Co-occurrence features provide the inter pixel relationship which is useful for ...
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Hyperspectral Image Classification based on Dimensionality Reduction and Swarm Optimization Approach
... spectral-spatial classification approach is introduced to improve the classification accuracy of hyperspectral ...input image will be reduced in dimension by using Discriminant independent ...
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An Efficient Objects Discrimination and Noise Reduction On Hyperspectral Images
... Abstract— Hyperspectral imaging (HSI) combines conventional imaging and spectroscopy to attain both spatial and spectral information from an ...a hyperspectral image limits its application and has a ...
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Advanced Spectral and Spatial Techniques for Hyperspectral Image Analysis and Classification
... for hyperspectral image classification, ...the hyperspectral image ...and classification ac- ...of classification accuracy, while in terms of computational time it is ...
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