Robust Superpixel Segmentation for Hyperspectral-Image Restoration [PDF]
Entropy, 2023 Hyperspectral-image (HSI) restoration plays an essential role in remote sensing image processing. Recently, superpixel segmentation-based the low-rank regularized methods for HSI restoration have shown outstanding performance.
Ya-Ru Fan
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Superpixel Segmentation Based on Anisotropic Edge Strength [PDF]
Journal of Imaging, 2019 Superpixel segmentation can benefit from the use of an appropriate method to measure edge strength. In this paper, we present such a method based on the first derivative of anisotropic Gaussian kernels.
Gang Wang, Bernard De Baets
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Multiple Superpixel Graphs Learning Based on Adaptive Multiscale Segmentation for Hyperspectral Image Classification [PDF]
Remote Sensing, 2022 Hyperspectral image classification (HSIC) methods usually require more training samples for better classification performance. However, a large number of labeled samples are difficult to obtain because it is cost- and time-consuming to label an HSI in a ...
Chunhui Zhao +3 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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Enhanced Atrous Extractor and Self-Dynamic Gate Network for Superpixel Segmentation [PDF]
Applied Sciences, 2023 A superpixel is a group of pixels with similar low-level and mid-level properties, which can be seen as a basic unit in the pre-processing of remote sensing images. Therefore, superpixel segmentation can reduce the computation cost largely.
Bing Liu +3 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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Boundary-preserving superpixel segmentation
Journal of Applied Science and EngineeringIn recent years, superpixel segmentation has been widely used in image processing tasks as a preprocessing step. Superpixel segmentation aims to group pixels into homogeneous regions while maintaining edges.
Yuejia Lin +3 more
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FPGA acceleration of superpixel segmentation
, 2020 Superpixel segmentation is a preprocessing step for computer vision applications, where an image is split into segments referred to as superpixels. Then running the main algorithm on these superpixels reduces the number of data points processed in comparison to running the algorithm on pixels directly, while still keeping much of the same information ...
Magnus Östgren
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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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POSE-FCN SUPERPIXEL SEGMENTATION FOR BUILDING FACADES BASED ON 2D TEXTURE AND 3D LOCAL POSE-VARIED SEMANTIC FEATURES [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 The extraction of building facades based on image sequences has a great contribution to the construction of digital realistic cities. The superpixel segmentation algorithm is a pre-processing tool for segmentation because of its advantages of fast speed,
R. Zhang +5 more
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