… Since then, spectral–spatial classification has witnessed a … –spatial classification
methodologies for hyperspectral images, … – spatial classification methods. There are many …

… A simple yet powerful filtering approach has been proposed for spectral–spatial hyperspectral
image classification. The proposed method aims at optimizing the pixelwise classification …

… Fusion of spectral and spatial information is an effective way in improving the … hyperspectral
image classification. In this paper, a novel spectral–spatial hyperspectral image classification …

… In this paper, we have proposed a new approach for hyperspectral image classification using
spectral–spatial information under Bayesian inferring framework. First, the SMLR method is …

… characteristics of hyperspectral data make the accurate classification of such data challenging
for traditional machine learning methods. In addition, hyperspectral imaging often deals …

… Here, we introduce the proposed spatial-constraint hyperspectral image classification
method shown in Fig. 1. We first present the hyperspectral hypergraph construction process, …

… , we propose a hyperspectral image (HSI) classification method using spectral-spatial long
short … image patches centered at each pixel from it. After that, we feed the row vectors of each …

… Liu, “Spectral–spatial classification of hyperspectral image … Spectral–spatial classification of
hyperspectral images using … , “Spectral–spatial hyperspectral image classification with edge-…

Convolutional neural networks (CNNs) exhibit good performance in image processing tasks,
pointing themselves as the current state-of-the-art of deep learning methods. However, the …

… a powerful tool in classification of hyperspectral images (HSIs). The spatial context of an HSI
… the complementary yet correlated information for classification, a multiscale adaptive sparse …