Results 1 to 10 of about 5,165 (221)
Superpixel Embedding Network [PDF]
IEEE Transactions on Image Processing, 2020 Superpixel segmentation is a fundamental computer vision technique that finds application in a multitude of high level computer vision tasks. Most state-of-the-art superpixel segmentation methods are unsupervised in nature and thus cannot fully utilize frequently occurring texture patterns or incorporate multiscale context.
Utkarsh Gaur, B. S. Manjunath
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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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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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A Superpixel-by-Superpixel Clustering Framework for Hyperspectral Change Detection
Remote Sensing, 2022 Hyperspectral image change detection (HSI-CD) is an interesting task in the Earth’s remote sensing community. However, current HSI-CD methods are feeble at detecting subtle changes from bitemporal HSIs, because the decision boundary is partially stretched by strong changes so that subtle changes are ignored.
Qiuxia Li +12 more
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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
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Improved Spatial-Spectral Superpixel Hyperspectral Unmixing
Remote Sensing, 2019 In this paper, an unsupervised unmixing approach based on superpixel representation combined with regional partitioning is presented. A reduced-size image representation is obtained using superpixel segmentation where each superpixel is represented by ...
Mohammed Q. Alkhatib +1 more
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Color detection of printing based on improved superpixel segmentation algorithm [PDF]
Scientific ReportsWe propose an improved superpixel segmentation algorithm based on visual saliency and color entropy for online color detection in printed products. This method addresses the issues of low accuracy and slow speed in detecting color deviations in print ...
Hongwu Zhan +4 more
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Cluster Sensing Superpixel and Grouping
2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2016 Superpixel algorithms have shown significant potential in computer vision applications since they can be used to accelerate other computationally demanding algorithms. However, in contrast to the original purpose of superpixels, many upper layer methods still suffer from computational problems when incorporating superpixel for speedup.
Rui Li 0054, Lu Fang 0001
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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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