Results 1 to 10 of about 2,715 (183)
A Novel Spectral–Spatial Classification Method for Hyperspectral Image at Superpixel Level
Applied Sciences (Switzerland), 2020 Although superpixel segmentation provides a powerful tool for hyperspectral image (HSI) classification, it is still a challenging problem to classify an HSI at superpixel level because of the characteristics of adaptive size and shape of superpixels ...
Fuding Xie
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Multiscale superpixel depth feature extraction for hyperspectral image classification [PDF]
Scientific ReportsRecently, superpixel segmentation has been widely employed in hyperspectral image (HSI) classification of remote sensing. However, the structures of land-covers in HSI commonly vary greatly, which makes it difficult to fully fit the boundaries of land ...
Qi Yan +3 more
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Multiscale Superpixel Segmentation With Deep Features for Change Detection
IEEE Access, 2019 In this paper, a novel change detection technique is proposed based on multiscale superpixel segmentation and stacked denoising autoencoders (SDAE). This approach is designed to achieve superpixel-based change detection, in which the basic analysis unit ...
, Jiao Shi, Jiao Shi
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Superpixel Generation for SAR Imagery Based on Fast DBSCAN Clustering With Edge Penalty
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 In this article, we propose an adaptive superpixel generation algorithm for synthetic aperture radar (SAR) imagery, which is implemented based on fast density-based spatial clustering of applications with noise (DBSCAN) clustering and superpixel merging ...
Liang Zhang +5 more
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Extended set of superpixel features
Компьютерная оптика, 2021 Superpixel-based image processing and analysis methods usually use a small set of superpixel features. Expanding the description of superpixels can improve the quality of processing algorithms. In the paper, a set of 25 basic superpixel features of shape,
A.A. Egorova, V.V. Sergeyev
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SUPERPIXEL CLASSIFICATION OF HIGH SPATIAL RESOLUTION REMOTE SENSING IMAGE BASED ON MULTI-SCALE CNN AND SCALE PARAMETER ESTIMATION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2019 In recent years, considerable attention has been paid to integrate convolutional neural network (CNN) with land cover classification of high spatial resolution remote sensing image.
Y. Chen, D. Ming
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 The convolutional neural network (CNN) has a poor performance in nonuniform and edge regions due to the limitation of fixed receptive field. At the same time, feature stacking of input data can bring burden and overfitting to the network.
Ronghua Shang +5 more
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Scale‐adaptive superpixels for medical images
Quantitative Biology, 2022 Background Superpixel segmentation is a powerful preprocessing tool to reduce the complexity of image processing. Traditionally, size uniformity is one of the significant features of superpixels. However, in medical images, in which subjects scale varies
Limin Sun, Dongyang Ma, Yuanfeng Zhou
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Adaptive Superpixel Segmentation of Marine SAR Images by Aggregating Fisher Vectors
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Superpixel segmentation is an important technique for image analysis. In this article, we develop a new superpixel segmentation approach and investigate its application on ship target detection in marine synthetic aperture radar (SAR) images.
Xueqian Wang +3 more
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A Hybrid Model Based on Superpixel Entropy Discrimination for PolSAR Image Classification
Remote Sensing, 2022 Superpixel segmentation is widely used in polarimetric synthetic aperture radar (PolSAR) image classification. However, the classification method using simple majority voting cannot easily handle evidence conflicts in a single superpixel.
Jili Sun, Lingdong Geng, Yize Wang
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