Results 181 to 190 of about 3,600 (211)
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Superpixel Endmember Detection
IEEE Transactions on Geoscience and Remote Sensing, 2010Superpixels are homogeneous image regions comprised of multiple contiguous pixels. Superpixel representations can reduce noise in hyperspectral images by exploiting the spatial contiguity of scene features. This paper combines superpixels with endmember extraction to produce concise mineralogical summaries that assist in browsing large image catalogs ...
David R. Thompson 0001 +3 more
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Spherical superpixel segmentation
2016 IEEE International Conference on Multimedia and Expo (ICME), 2016In this paper, we present a superpixel generation method for spherical images, which cover 360° field-of-view. Unlike previous works that directly use existing superpixel algorithms on unrolled spherical images, our approach explicitly considers the geometry for spherical images and uses sphere as the underlying representation.
Qiang Zhao 0005, Liang Wan, Jiawan Zhang
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Signal, Image and Video Processing, 2013
Superpixels provide an over-segmentation representation of a natural image. However, they lack information of the entire object. In this paper, we propose a method to obtain superpixels through a merging strategy based on the bottom-up saliency values of superpixels.
Linfeng Xu 0001 +2 more
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Superpixels provide an over-segmentation representation of a natural image. However, they lack information of the entire object. In this paper, we propose a method to obtain superpixels through a merging strategy based on the bottom-up saliency values of superpixels.
Linfeng Xu 0001 +2 more
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Weighted superpixel segmentation
The Visual Computer, 2019Image boundaries and regularity are two important factors in superpixel segmentation. Balancing the influence of image boundaries and regularity is key to producing superpixels. In this paper, we present a novel superpixel segmentation algorithm, called weighted superpixel segmentation (WSS), which is capable of generating superpixels with high ...
Xin Qian +2 more
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Superpixel segmentation: A benchmark
Signal Processing: Image Communication, 2017Abstract Various superpixel approaches have been published recently. These algorithms are assessed using different evaluation metrics and datasets resulting in discrepancy in algorithm comparison. This calls for a benchmark to compare the state-of-the-arts methods and evaluate their pros and cons.
Murong Wang +4 more
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Benchmarking superpixel descriptors
2015 23rd European Signal Processing Conference (EUSIPCO), 2015Superpixels are useful intermediate representations for many computer vision tasks. While the segmentation step is well studied, the subsequent creation of meaningful descriptors lacks this foundation. Superpixels have similar properties like affine covariant regions (keypoints), but there are fundamental differences that led to a different set of ...
Peer Neubert, Peter Protzel
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Spherical Superpixel Segmentation
IEEE Transactions on Multimedia, 2018These days, superpixel algorithms are widely used in computer vision and multimedia applications. However, existing algorithms are designed for planar images, which are less suited to deal with wide angle images. In this paper, we present a superpixel segmentation method for $\text{360}^\circ$ spherical images.
Qiang Zhao 0005 +5 more
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Constrained Superpixel Tracking
IEEE Transactions on Cybernetics, 2018In this paper, we propose a constrained graph labeling algorithm for visual tracking where nodes denote superpixels and edges encode the underlying spatial, temporal, and appearance fitness constraints. First, the spatial smoothness constraint, based on a transductive learning method, is enforced to leverage the latent manifold structure in feature ...
Lijun Wang +2 more
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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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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 0001 +2 more
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