Results 61 to 70 of about 9,095 (206)

Updated Homogeneity Criteria Based Low-Dimensional Representation for Hyperspectral Unmixing

IEEE Access
Superpixel-based approaches have been proposed for hyperspectral unmixing. The basic assumption of this approach is that the superpixel over-segmentation segments the image into small homogeneous areas.
Jiarui Yi, Huiyi Gao
doaj   +1 more source

A Bridge Transformer Network With Deep Graph Convolution for Hyperspectral Image Classification

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Transformers have been widely applied to hyperspectral image classification, leveraging their self‐attention mechanism for powerful global modelling. However, two key challenges remain as follows: excessive memory and computational costs from calculating correlations between all tokens (especially as image size or spectral bands increase) and ...
Yuquan Gan, Siyu Wu, Chang Su, Nan Xiang, Zhijie Xu, Yushan Pan   +5 more
wiley   +1 more source

Improved Cost Aggregation Algorithm for Fast Stereo Matching [PDF]

Jisuanji gongcheng, 2019
For the cost aggregation problem in stereo matching,an improved cost aggregation algorithm is proposed.The image is segmented by superpixel and the Minimum Spanning Tree(MST) is established.Then,use tree filter for cost aggregation to generate superpixel
YANG Gang, JIN Tao, WANG Dawei, CAO Jingjin, ZHANG Na, YAN Biwu, LI Tao, CHENG Yuan
doaj   +1 more source

A deep learning‐enabled toolkit for the 3D segmentation of ventricular cardiomyocytes

The Journal of Physiology, EarlyView.
Abstract figure legend 3D cardiomyocyte segmentation enables comprehensive analyses of myocardial microstructure in health and disease; however, it is technically demanding. We present an open‐source toolkit for this task, which reduces challenges associated with sample preparation, image restoration, segmentation and proofreading.
Joachim Greiner, Fabio Frangiamore, Frédéric Sonak, Josef Madl, Thomas Seidel, Peter Kohl, Eva A. Rog‐Zielinska   +6 more
wiley   +1 more source

Geometry-based Superpixel Segmentation - Introduction of Planar Hypothesis for Superpixel Construction

Proceedings of the 10th International Conference on Computer Vision Theory and Applications, 2015
Superpixel segmentation is widely used in the preprocessing step of many applications. Most of existing methods are based on a photometric criterion combined to the position of the pixels. In the same way as the Simple Linear Iterative Clustering (SLIC) method, based on k-means segmentation, a new algorithm is introduced.
Bauda, Marie-Anne, Chambon, Sylvie, Gurdjos, Pierre, Charvillat, Vincent   +3 more
openaire   +2 more sources

Robust Active Contour Model for Image Segmentation Using a Probability Density Function Approach

IET Image Processing, Volume 20, Issue 1, January/December 2026.
This paper proposes an active contour model‐based image segmentation algorithm using the probability density function. Initially, the probability density function is defined by the local mean and variance. Next, a length penalty term and a distance regularization term are incorporated.
XinChao Meng, Si Si, Pei Zhang
wiley   +1 more source

Semantic Segmentation of High-Resolution Remote Sensing Imagery via an End-to-End Graph Attention Network With Superpixel Embedding

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Semantic segmentation of high-resolution remote sensing images is crucial in ecological evaluation, natural resource surveys, etc. Compared with CNN-based and transformer-based methods, graph neural networks (GNNs) have drawn increasing attention because
Ying Tang, Xiangyun Hu, Tao Ke, Mi Zhang
doaj   +1 more source

Multiscale Superpixel-Guided Weighted Graph Convolutional Network for Polarimetric SAR Image Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Polarimetric synthetic aperture radar (PolSAR) has attracted more attentions because of its excellent observation ability, and PolSAR image classification has become one of the significant tasks in remote sensing interpretation.
Ru Wang, Yinju Nie, Jie Geng
semanticscholar   +1 more source

Efficient Color Quantization Using Superpixels

Sensors, 2022
We propose three methods for the color quantization of superpixel images. Prior to the application of each method, the target image is first segmented into a finite number of superpixels by grouping the pixels that are similar in color. The color of a superpixel is given by the arithmetic mean of the colors of all constituent pixels.
Mariusz Frackiewicz, Henryk Palus
openaire   +3 more sources

Multiscale Superpixel-Based Sparse Representation for Hyperspectral Image Classification †

Remote Sensing, 2017
Recently, superpixel segmentation has been proven to be a powerful tool for hyperspectral image (HSI) classification. Nonetheless, the selection of the optimal superpixel size is a nontrivial task.
Shuzhen Zhang, Shutao Li, Wei Fu, Leiyuan Fang   +3 more
doaj   +1 more source