Results 11 to 20 of about 9,167 (192)

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
doaj   +6 more sources

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
doaj   +2 more sources

Color detection of printing based on improved superpixel segmentation algorithm [PDF]

Scientific Reports
We 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, Yuhao Shou, Lidu Wen, Fang Xu, Libin Zhang   +4 more
doaj   +2 more sources

Superpixel Segmentation Using Gaussian Mixture Model [PDF]

IEEE Transactions on Image Processing, 2018
Superpixel segmentation algorithms are to partition an image into perceptually coherence atomic regions by assigning every pixel a superpixel label. Those algorithms have been wildly used as a preprocessing step in computer vision works, as they can enormously reduce the number of entries of subsequent algorithms.
Zhihua Ban, Jianguo Liu, Li Cao
openaire   +6 more sources

Multiscale superpixel depth feature extraction for hyperspectral image classification [PDF]

Scientific Reports
Recently, 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, Shuzhen Zhang, Xiang Chen, Ziyou Zheng   +3 more
doaj   +2 more sources

Multiscale Superpixel Segmentation With Deep Features for Change Detection

IEEE Access, 2019
In this paper, a novel change detection technique is proposed based on multiscale superpixel segmentation and stacked denoising autoencoders (SDAE). This approach is designed to achieve superpixel-based change detection, in which the basic analysis unit ...
Yu Lei, Xiaodong Liu, Jiao Shi, Chao Lei, Jing Wang   +4 more
doaj   +3 more sources

Boundary-preserving superpixel segmentation

Journal of Applied Science and Engineering
In 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, Zhao Li, Chenxun Yuan, Yi Liu   +3 more
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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, You He, Gang Li, Antonio Plaza   +3 more
doaj   +1 more source

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, R. Zhang, Y. He, X. Yi, G. Lu, X. Guo   +5 more
doaj   +1 more source

TSSP-UNet: A Two-Stage Weakly Supervised Pathological Image Segmentation With Point Annotations. [PDF]

IET Syst Biol
Deep convolutional neural networks excel at image segmentation but face challenges with complex instance training and high‐precision annotation acquisition. This study proposes TSSP‐UNet, a two‐stage weakly supervised segmentation approach: the first stage trains a segmentation network with constraint and attention mechanisms plus a feature aggregation
Wang S, Shi G, Wang Y, Li Q, Zhao Y, Cheng X.   +5 more
europepmc   +2 more sources