Results 41 to 50 of about 1,822 (166)

Iterative Boundaries Implicit Identification for Superpixels Segmentation: A Real-Time Approach

IEEE Access, 2021
Superpixel algorithms group visually coherent pixels and form an alternative representation of the regular structure of the pixel grid. This fundamental low-level computer vision preprocessing step greatly reduces the complexity of subsequent image ...
Serge Bobbia, Richard Macwan, Yannick Benezeth, Keisuke Nakamura, Randy Gomez, Julien Dubois   +5 more
doaj   +1 more source

Segmenting Planar Superpixel Adjacency Graphs w.r.t. Non-planar Superpixel Affinity Graphs [PDF]

, 2013
We address the problem of segmenting an image into a previously unknown number of segments from the perspective of graph partitioning. Specifically, we consider minimum multicuts of superpixel affinity graphs in which all affinities between non-adjacent superpixels are negative.
Andres, B., Yarkony, J., Manjunath, B., Kirchhoff, S., Turetken, E., Fowlkes, C., Pfister, H.   +6 more
openaire   +2 more sources

Fast Segmentation and Classification of Very High Resolution Remote Sensing Data Using SLIC Superpixels

Remote Sensing, 2017
Speed and accuracy are important factors when dealing with time-constraint events for disaster, risk, and crisis-management support. Object-based image analysis can be a time consuming task in extracting information from large images because most of the ...
Ovidiu Csillik
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

Mapping Dongting Lake Wetland Utilizing Time Series Similarity, Statistical Texture, and Superpixels With Sentinel-1 SAR Data

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
Wetland is of significant ecological value, which is very important and challenging for large-scale mapping. Sentinel-1 can continuously record wetland changes with its all-day, all-weather working capability.
Hui Yang, Xiuguo Liu, Qihao Chen, Yuanye Cao   +3 more
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

Dark Spot Detection from SAR Images Based on Superpixel Deeper Graph Convolutional Network

Remote Sensing, 2022
Synthetic Aperture Radar (SAR) is the primary equipment used to detect oil slicks on the ocean’s surface. On SAR images, oil spill regions, as well as other places impacted by atmospheric and oceanic phenomena such as rain cells, upwellings, and internal
Xiaojian Liu, Yansheng Li, Xinyi Liu, Huimin Zou   +3 more
doaj   +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

Automatic Image Segmentation With Superpixels and Image-Level Labels

IEEE Access, 2019
Automatically and ideally segmenting the semantic region of each object in an image will greatly improve the precision and efficiency of subsequent image processing.
Xinlin Xie, Gang Xie, Xinying Xu, Lei Cui, Jinchang Ren   +4 more
doaj   +1 more source