Experiments conducted on two standard HSI datasets proved that the proposed multiscale scheme can improve the classification accuracy of both LBP and CLBP, and ...

Spatial information has shown significant contribution for hyperspectral image classification. Local Binary Pattern. (LBP) can be used for extracting ...

Experiments conducted on two standard HSI datasets proved that the proposed multiscale scheme can improve the classification accuracy of both LBP and CLBP, and ...

In this work we show that the morphological techniques can be integrated in this kind of classifiers using several composite feature mappings which are proposed ...

This paper proposes a multi-scale spectral–spatial attention network with frequency-domain lightweight Transformer (MSA-LWFormer) for HSI classification.

Combining spectral and spatial features can increase the land-cover classification accuracy of hyperspectral images (HSI), but improvements are still needed ...

Sep 15, 2021 · This paper introduces the idea of guided filtering into hyperspectral image classification, and then proposes a multi-scale guided feature extraction and ...

Jun 6, 2016 · Brushlet is a novel tool for image orientation analysis, whose energy feature is adopted in texture segmentation, image classification and ...

In recent years, convolutional neural networks (CNNs) have been widely used for hyperspectral image classification, which show good performance.

Jul 1, 2022 · The Multi-type Spectral Spatial Feature (MSSF) is constructed by PCA fusing with ISDF, NSDF, and a type of global texture feature. The global ...