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Linear Spectral Clustering Superpixel
IEEE Transactions on Image Processing, 2017In this paper, we present a superpixel segmentation algorithm called linear spectral clustering (LSC), which is capable of producing superpixels with both high boundary adherence and visual compactness for natural images with low computational costs. In LSC, a normalized cuts-based formulation of image segmentation is adopted using a distance metric ...
Jiansheng Chen, Zhengqin Li, Bo Huang
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Ship Detection in SAR Images Based on Multilevel Superpixel Segmentation and Fuzzy Fusion
IEEE Transactions on Geoscience and Remote Sensing, 2023Superpixel can maintain the boundary of the target and reduce the influence of speckle noise, which has been widely applied to synthetic aperture radar (SAR) image target detection.
Qian Sun +4 more
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2011 International Conference on Computer Vision, 2011
While numerous algorithms have been proposed for object tracking with demonstrated success, it remains a challenging problem for a tracker to handle large change in scale, motion, shape deformation with occlusion. One of the main reasons is the lack of effective image representation to account for appearance variation.
null Shu Wang +3 more
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While numerous algorithms have been proposed for object tracking with demonstrated success, it remains a challenging problem for a tracker to handle large change in scale, motion, shape deformation with occlusion. One of the main reasons is the lack of effective image representation to account for appearance variation.
null Shu Wang +3 more
openaire +1 more source
2021 International Russian Automation Conference (RusAutoCon), 2021
This paper offers the simplest understanding of superpixels as maximal pixel clusters providing error-free obtaining of a limited sequence of accessible optimal piecewise constant image approximations with the minimum achievable approximation error (total squared error) E for each number of pixel clusters.
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This paper offers the simplest understanding of superpixels as maximal pixel clusters providing error-free obtaining of a limited sequence of accessible optimal piecewise constant image approximations with the minimum achievable approximation error (total squared error) E for each number of pixel clusters.
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2015 IEEE International Conference on Image Processing (ICIP), 2015
As a pre-processing tool, superpixel algorithms have been popular used in many computer-vision applications. High efficiency is a desired property of superpixel algorithms, especially in real-time vision systems. In this paper, a novel high-efficient superpixel algorithm is developed based on the watershed algorithm, namely the spatial-constrained ...
Zhongwen Hu, Qin Zou, Qingquan Li
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As a pre-processing tool, superpixel algorithms have been popular used in many computer-vision applications. High efficiency is a desired property of superpixel algorithms, especially in real-time vision systems. In this paper, a novel high-efficient superpixel algorithm is developed based on the watershed algorithm, namely the spatial-constrained ...
Zhongwen Hu, Qin Zou, Qingquan Li
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Detection of Moving Object Using Superpixel Fusion Network
ACM Trans. Multim. Comput. Commun. Appl., 2023Moving object detection is still a challenging task in complex scenes. The existing methods based on deep learning mainly use U-Nets and have achieved amazing results. However, they ignore the local continuity between pixels.
Yang Li
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Differential Evolutionary Superpixel Segmentation
IEEE Transactions on Image Processing, 2018Superpixel segmentation has been of increasing importance in many computer vision applications recently. To handle the problem, most state-of-the-art algorithms either adopt a local color variance model or a local optimization algorithm. This paper develops a new approach, named differential evolutionary superpixels, which is able to optimize the ...
Yue-Jiao Gong, Yicong Zhou
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High Quality Superpixel Generation Through Regional Decomposition
IEEE transactions on circuits and systems for video technology (Print), 2023Superpixel generation is increasingly an important area for computer vision tasks. While superpixels with highly regular shapes are preferred to make the subsequent processing easier, the accuracy of the superpixel boundaries is also necessary.
Yunyang Xu +4 more
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Superpixel Guided Deformable Convolution Network for Hyperspectral Image Classification
IEEE Transactions on Image Processing, 2022Convolutional neural networks are widely used in the field of hyperspectral image classification because of their excellent nonlinear feature extraction ability.
Chunhui Zhao, Wenxiang Zhu, Shou Feng
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Content-Adaptive Superpixel Segmentation
IEEE Transactions on Image Processing, 2018Superpixel segmentation targets at grouping pixels in an image into atomic regions whose boundaries align well with the natural object boundaries. This paper first proposes a new feature representation for superpixel segmentation that holistically embraces color, contour, texture, and spatial features.
Xiaolin Xiao, Yicong Zhou, Yue-Jiao Gong
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