[PDF] Top 20 Superpixel based feature specific sparse representation for spectral-spatial classification of hyperspectral images
Has 10000 "Superpixel based feature specific sparse representation for spectral-spatial classification of hyperspectral images" found on our website. Below are the top 20 most common "Superpixel based feature specific sparse representation for spectral-spatial classification of hyperspectral images".
Superpixel based feature specific sparse representation for spectral-spatial classification of hyperspectral images
... The sparse representation classification (SRC)-based method has been found to be a powerful tool for numerous computer vision ...a sparse dictionary using a few training samples, the ... See full document
17
Sparse representation-based augmented multinomial logistic extreme learning machine with weighted composite features for spectral-spatial classification of hyperspectral images
... rich spectral and spatial information contained in a three-dimensional hypercube, hyperspectral images (HSI) provide a unique way for characterizing objects in geographical scenes, especially ... See full document
15
Linear vs. nonlinear extreme learning machine for spectral-spatial classification of hyperspectral images
... is based on the urban image collected in June 1992 by the AVIRIS sensors over the Indian Pines region in North-western ...200 spectral bands after removing 20 water absorption bands ranging from ... See full document
15
Frontiers in Spectral-Spatial Classification of Hyperspectral Images
... HSI classification is given by Markov random fields (MRF), which provide powerful and flexible spatial-contextual models for the prior distribution in Bayesian image analysis ...HSI classification in ... See full document
32
Spectral–Spatial Classification of Hyperspectral Images Based on Hidden Markov Random Fields
... and classification steps, first, the number of pixels with different class labels in each object is ...the classification step) in the ...homogeneous classification maps in comparison with ... See full document
11
Spatial-spectral classification of hyperspectral images : a deep learning framework with Markov random fields based modeling
... analysis, classification and target detection, deep learning has also been introduced [27]-[30], because of its powerful capacity of unsupervised deep features self- ...HSI classification based on ... See full document
13
Spectral-spatial classification of hyperspectral data using spectral-domain local binary patterns
... in spectral-spatial features classification for hyperspectral images (HSI) with high spatial ...novel Spectral-spatial classification method for improving ... See full document
23
Joint bilateral filtering and spectral similarity-based sparse representation : a generic framework for effective feature extraction and data classification in hyperspectral imaging
... of hyperspectral images (HSI) has been a challenging problem under active investigation for years especially due to the extremely high data dimensionality and limited number of samples available for ...that ... See full document
22
Spatial-spectral classification of hyperspectral images : a deep learning framework with Markov random fields based modeling
... analysis, classification and target detection, deep learning has also been introduced [27]-[30], because of its powerful capacity of unsupervised deep features self- ...HSI classification based on ... See full document
12
Spectral-spatial classification of hyperspectral data using spectral-domain local binary patterns
... in spectral-spatial features classification for hyperspectral images (HSI) with high spatial ...novel Spectral-spatial classification method for improving ... See full document
22
Spatial and Spectral Nonparametric Linear Feature Extraction Method for Hyperspectral Image Classification
... recognition. Feature extraction aims to reduce the d imens iona lity of the high-d imens iona l dataset to enhanc e the clas- sification accuracy and foster the classification speed, particularly when the ... See full document
5
Local block multilayer sparse extreme learning machine for effective feature extraction and classification of hyperspectral images
... the classification of hyperspectral images (HSIs), they still suffer from three main ...Ineffective feature extraction in HSIs due to a single hidden layer neuron network used; 2) ill-posed ... See full document
15
Multiscale spatial-spectral convolutional network with image-based framework for hyperspectral imagery classification
... using spatial and spectral information has been widely applied to hyperspectral image (HSI) ...detailed representation of features. However, most of CNN-based HSI classification ... See full document
21
Unsupervised Spectral-Spatial Feature Learning via Deep Residual Conv-Deconv Network for Hyperspectral Image Classification
... unsupervised feature learning, which has a quick access to arbitrary amounts of unlabeled data, is conceptually of high ...unsupervised spectral–spatial feature learning of ... See full document
16
Cone-based joint sparse modelling for hyperspectral image classification
... Recently, sparse representation has been extensively investigated in hy- perspectral imaging ...A hyperspectral image (HSI) is a 3-dimensional data cube with two spatial dimensions and one ... See full document
46
Local block multilayer sparse extreme learning machine for effective feature extraction and classification of hyperspectral images
... the classification of hyperspectral images (HSIs), they still suffer from three main ...Ineffective feature extraction in HSIs due to a single hidden layer neuron network used; 2) ill-posed ... See full document
14
Advanced Spectral and Spatial Techniques for Hyperspectral Image Analysis and Classification
... of hyperspectral data can provide a better character- ization of the spectral behaviour of different land-covers, however the redun- dancy of information should be detected and discarded in order to improve ... See full document
172
Classification of hyperspectral images by exploiting spectral-spatial information of superpixel via multiple kernels
... Shutao Li (M’07-SM’15) received his B.S., M.S., and Ph.D. degrees in electrical engineering from the Hunan University, in 1995, 1997, and 2001, respectively. He joined the College of Electrical and Information ... See full document
32
Group sparse representation based on nonlocal spatial and local spectral similarity for hyperspectral imagery classification
... for hyperspectral imagery (HSI), increase the possibility of more accurate discrimination of materials of interest ...of classification is to assign a unique label to each pixel vector, such that it can be ... See full document
19
Spectral-spatial feature learning for hyperspectral imagery classification using deep stacked sparse autoencoder
... learning-based classification involves making a deep architecture for the pixel-based data representation and classification by extracting more robust and abstract descriptors to ... See full document
16
Related subjects