Results 31 to 40 of about 5,165 (221)
Superpixel-Level Weighted Label Propagation for Hyperspectral Image Classification
, 2020 As a typical graph-based semisupervised learning technique, the label propagation (LP) approach has gained much attention in recent years. The key to LP algorithms is the propagation capability and efficiency of the similarity matrix, which describes the
Jia, Sen +4 more
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Superpixel Nonlocal Weighting Joint Sparse Representation for Hyperspectral Image Classification
Remote Sensing, 2022 Joint sparse representation classification (JSRC) is a representative spectral–spatial classifier for hyperspectral images (HSIs). However, the JSRC is inappropriate for highly heterogeneous areas due to the spatial information being extracted from a ...
Aizhu Zhang +7 more
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Superpixels, Occlusion and Stereo [PDF]
2011 International Conference on Digital Image Computing: Techniques and Applications, 2011 Graph-based energy minimization is now the state of the art in stereo matching methods. In spite of its outstanding performance, few efforts have been made to enhance its capability of occlusion handling. We propose an occlusion constraint, an iterative optimization strategy and a mechanism that proceeds on both the digital pixel level and the super ...
Yuhang Zhang 0001 +3 more
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Remote Sensing, 2021 This paper presents a composite kernel method (MWASCK) based on multiscale weighted adjacent superpixels (ASs) to classify hyperspectral image (HSI). The MWASCK adequately exploits spatial-spectral features of weighted adjacent superpixels to guarantee ...
Yaokang Zhang, Yunjie Chen
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Remote Sensing, 2019 To improve the performance of the sparse representation classification (SRC), we propose a superpixel-based feature specific sparse representation framework (SPFS-SRC) for spectral-spatial classification of hyperspectral images (HSI) at superpixel level.
He Sun +5 more
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Earth remote sensing data processing for obtaining vegetation types maps [PDF]
Компьютерная оптика, 2018 In this paper, we propose an earth remote sensing data processing technology for obtaining vegetation types maps. The technology includes the following steps: obtaining superpixel representation of an image, calculating superpixel features, K-Means ...
Anna Varlamova +2 more
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Superpixel-based saliency detection [PDF]
, 2013 International audienceIn this paper, we propose an effective superpixel-based saliency model. First, the original image is simplified by performing superpixel segmentation and adaptive color quantization.
Luo, Shuhua +5 more
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingAccurate superpixel segmentation of ocean remote sensing data plays a crucial role in the success of monitoring the changes on the ocean surface. Recently, so many superpixel segmentation methods have attracted much attention to ocean remote sensing ...
Qianna Cui, Haiwei Pan, Kejia Zhang
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A Two-Stage Gradient Ascent-Based Superpixel Framework for Adaptive Segmentation
Applied Sciences, 2019 Superpixel segmentation usually over-segments an image into fragments to extract regional features, thus linking up advanced computer vision tasks. In this work, a novel coarse-to-fine gradient ascent framework is proposed for superpixel-based color ...
Wangpeng He +4 more
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Superpixel Boundary-Based Edge Description Algorithm for SAR Image Segmentation
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020 Although various methods can effectively segment synthetic aperture radar (SAR) images, we found that the method combining superpixel and image edge information can get better results. To solve the problem that common SAR image segmentation methods often
Ronghua Shang +4 more
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