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Spherical superpixel segmentation

2016 IEEE International Conference on Multimedia and Expo (ICME), 2016
In 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, Liang Wan, Jiawan Zhang
openaire   +1 more source

Weighted superpixel segmentation

The Visual Computer, 2019
Image 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, Xuemei Li, Caiming Zhang
openaire   +1 more source

Spherical Superpixel Segmentation

IEEE Transactions on Multimedia, 2018
These 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   +5 more
openaire   +1 more source

Revisiting SLIC: Fast Superpixel Segmentation of Marine SAR Images Using Density Features

IEEE Transactions on Geoscience and Remote Sensing, 2022
The simple linear iterative clustering (SLIC) has been shown as an efficient and widely used superpixel-based algorithm for segmenting marine synthetic aperture radar (SAR) images.
Xueqian Wang, Gang Li, A. Plaza, You He
semanticscholar   +1 more source

Superpixel Convolution for Segmentation

2018 25th IEEE International Conference on Image Processing (ICIP), 2018
In this paper, we propose a novel segmentation algorithm based on convolutional neural networks (CNNs) on superpix-else CNNs are powerful methods for several computer vision tasks, but spatial information disappears through the pooling process.
Teppei Suzuki   +3 more
openaire   +1 more source

Superpixel Segmentation-Based Evolutionary Multitasking Algorithm for Feature Selection of Hyperspectral Images

IEEE Transactions on Evolutionary Computation
Feature selection (FS) is a very important technique for hyperspectral image (HSI) classification, as successfully selecting informative features can significantly increase the learning performance while reducing the computational cost.
Lingjie Li   +5 more
semanticscholar   +1 more source

Fast Graph Algorithms for Superpixel Segmentation

IEEE Conference on High Performance Extreme Computing, 2022
We introduce the novel graph-based algorithm SLAM (simultaneous local assortative mixing) for fast and high-quality superpixel segmentation of any large color image.
D. Floros   +3 more
semanticscholar   +1 more source

Dynamic Random Walk for Superpixel Segmentation

IEEE Transactions on Image Processing, 2020
In this paper, we propose a novel random walk model, called Dynamic Random Walk (DRW), which adds a new type of dynamic node to the original RW model and reduces redundant calculation by limiting the walk range. To solve the seed-lacking problem of the proposed DRW, we redefine the energy function of the original RW and use the first arrival ...
Xuejing Kang, Lei Zhu, Anlong Ming
openaire   +2 more sources

A Comprehensive Review and New Taxonomy on Superpixel Segmentation

ACM Computing Surveys
Superpixel segmentation consists of partitioning images into regions composed of similar and connected pixels. Its methods have been widely used in many computer vision applications, since it allows for reducing the workload, removing redundant ...
Isabela Borlido Barcelos   +5 more
semanticscholar   +1 more source

Improving color homogeneity measure in superpixel segmentation assessment

SIBGRAPI Conference on Graphics, Patterns and Images, 2022
The quality of a superpixel segmentation may consider accuracy in delineation, shape compactness, and color homogeneity. Among several existing measures, Explained Variation (EV) and Intra-cluster Variation (IV) seem to be the only ones focusing on color
Isabela Borlido Barcelos   +4 more
semanticscholar   +1 more source

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