Spectral-spatial Processing in Hyperspectral Image Classification
On the Sampling Strategy for Evaluation of Spectral-Spatial Methods in Hyperspectral Image Classification
... Abstract—Spectral-spatial processing has been increasingly explored in remote sensing hyperspectral image ...the classification accuracy, experimental setting and design for ...
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Spectral-spatial Feature Extraction for Hyperspectral Image Classification
... disperse globally and randomly. The partition referred here is a group of connect- ed pixels with the same labels. For each class, there are usually several partitions distributed on the map, corresponding to the land ...
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Integration of Spatial and Spectral Information for Hyperspectral Image Classification
... from spectral and spatial domain for classification presents the potential for increased classification performance for hyperspectral image ...pixel-wise classification ...
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Advanced Spectral and Spatial Techniques for Hyperspectral Image Analysis and Classification
... of hyperspectral remote sensing images, placing the focal point on the investigation and optimisation techniques for the extraction and integration of spectral and spatial ...the spectral ...
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Deep Pyramidal Residual Networks for Spectral-Spatial Hyperspectral Image Classification
... sponding classification maps shown in Figs. 6, 7 and 8. On the one hand, spectral methods, such as SVM or MLP, tend to generate rather noisy classification maps because they do not take into account ...
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Spectral-spatial approaches for hyperspectral data classification
... labels. Spatial information can be used to overcome the salt-and- pepper artifacts of the classification ...by spatial information to improve classification ...using spectral ...
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Frontiers in Spectral-Spatial Classification of Hyperspectral Images
... porating spatial information into an HSI classification ...of spatial information in the classification system can significantly im- prove classification accuracies compared to 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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Multiscale spatial-spectral convolutional network with image-based framework for hyperspectral imagery classification
... patch-based classification method will consume more time when processing a larger ...the image-based classification and the processing of testing phase is faster than the patch-based ...
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Hybrid Subspace Detection based on Spectral and Spatial Information for Effective Hyperspectral Image Classification
... 5.3 Result of Feature Selection Fig 3: Cumulative Variance of Pavia University dataset Higher variance does not give guarantee of consuming required information. Some features with lower variance may be further ...
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Unsupervised spectral sub-feature learning for hyperspectral image classification
... in hyperspectral image (HSI) ...the spectral domain, which allows e ff ective use of the correlated spectral ...the hyperspectral input pixels to an expanded but sparse feature ...
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Exploring Structural Consistency in Graph Regularized Joint Spectral-Spatial Sparse Coding for Hyperspectral Image Classification
... Abstract—In hyperspectral image classification, both spec- tral and spatial data distributions are important in describing and identifying different materials and objects in the ...consistent ...
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Spectral-spatial classification of hyperspectral data using spectral-domain local binary patterns
... individual classification pipeline and combines the distinct decisions into a final one with the ...overcome classification problem above in HSI, a new texture feature extraction algorithm which exploits ...
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Spectral-spatial classification of hyperspectral data using spectral-domain local binary patterns
... individual classification pipeline and combines the distinct decisions into a final one with the ...overcome classification problem above in HSI, a new texture feature extraction algorithm which exploits ...
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Spectral-spatial classification of hyperspectral imagery with 3D convolutional neural network
... for classification. As the spectral features and the spatial features are extracted simultaneously, this work takes full advantage of the structural characteristics of the 3D HSI ...full ...
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Hyperspectral Image Classification
... samples. Hyperspectral (HS) image classification always suffers from varieties of artifacts, such as high dimensionality, limited or unbalanced training samples [7], spectral variability, and ...
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Spectral and Spatial Cloud Detection Onboard for Hyperspectral Remote Sensing Image
... 198 Generally, k is set as 0.5 (between 0 to 1). ESAM amplifies the angular distance between two vectors. 199 After the 3-D original hyperspectral image I [L,W,H] processing by ESAM, we can obtain a ...
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Unsupervised Spectral-Spatial Feature Learning via Deep Residual Conv-Deconv Network for Hyperspectral Image Classification
... the hyperspectral image and own good description power for semantic visual patterns in the object ...unsupervised spectral–spatial feature learning possess strong selectiveness on patterns ...
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Hyperspectral Images Classification via Weighted Spatial Spectral Principle Component Analysis
... weighted spatial and spectral principle component analysis (WSSPCA) ...and spectral factor, which can effectively eliminating the influence of singular ...
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Spectral–Spatial Classification of Hyperspectral Images Based on Hidden Markov Random Fields
... recognition, image processing, and signal processing, and he has published extensively in those ...of Image and Data Fusion and was the Chairman of the Steering Committee of IEEE Journal of ...
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