Results 11 to 20 of about 495 (155)
Hyperspectral Imagery Classification Based on Multiscale Superpixel-Level Constraint Representation [PDF]
Remote Sensing, 2020 Sparse representation (SR)-based models have been widely applied for hyperspectral image classification. In our previously established constraint representation (CR) model, we exploited the underlying significance of the sparse coefficient and proposed ...
Haoyang Yu +5 more
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Advanced Hyperspectral Image Analysis: Superpixelwise Multiscale Adaptive T-HOSVD for 3D Feature Extraction [PDF]
SensorsHyperspectral images (HSIs) possess an inherent three-order structure, prompting increased interest in extracting 3D features. Tensor analysis and low-rank representations, notably truncated higher-order SVD (T-HOSVD), have gained prominence for this ...
Qiansen Dai, Chencong Ma, Qizhong Zhang
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IEEE Transactions on Geoscience and Remote Sensing, 2019 In virtue of the spatial structural characteristic of surface materials, the performance of the hyperspectral image classification can be boosted by incorporating texture information. Normally, the spatial structure can be extracted by predefined operators, including the popular extended multiattribute profiles (EMAPs) and the Gabor filters.
Sen Jia, Jiasong Zhu, Meng Xu
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingHyperspectral image (HSI) classification plays a crucial role in remote sensing applications, leveraging the rich spectral and spatial information inherent in HSI.
Tingting Wang, Yao Sun, Yunfeng Hu
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A Superpixel-Based Relational Auto-Encoder for Feature Extraction of Hyperspectral Images
Remote Sensing, 2019 Filter banks transferred from a pre-trained deep convolutional network exhibit significant performance in heightening the inter-class separability for hyperspectral image feature extraction, but weakening the intra-class consistency simultaneously.
Miaomiao Liang, Licheng Jiao, Zhe Meng
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Multiscale Union Regions Adaptive Sparse Representation for Hyperspectral Image Classification
Remote Sensing, 2017 Sparse Representation has been widely applied to classification of hyperspectral images (HSIs). Besides spectral information, the spatial context in HSIs also plays an important role in the classification.
Fei Tong +3 more
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Semantic Segmentation of Remote Sensing Imagery Based on Multiscale Deformable CNN and DenseCRF
Remote Sensing, 2023 The semantic segmentation of remote sensing images is a significant research direction in digital image processing. The complex background environment, irregular size and shape of objects, and similar appearance of different categories of remote sensing ...
Xiang Cheng, Hong Lei
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International Journal of Digital Earth, 2022 In map multiscale visualization, typification is the process of replacing original objects, such as buildings, using a smaller number of objects while maintaining initial geometrical and distribution characteristics.
Yilang Shen +4 more
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Remote Sensing, 2020 In this paper, superpixel features and extended multi-attribute profiles (EMAPs) are embedded in a multiple kernel learning framework to simultaneously exploit the local and multiscale information in both spatial and spectral dimensions for hyperspectral
Lei Pan, Chengxun He, Yang Xiang, Le Sun
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Remote Sensing, 2023 Convolutional neural networks (CNNs) and graph convolutional networks (GCNs) have led to promising advancements in hyperspectral image (HSI) classification; however, traditional CNNs with fixed square convolution kernels are insufficiently flexible to ...
Junru Yin +6 more
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