Article
Computer Science, Artificial Intelligence
Feng Huang, Yating Chen, Xuesong Wang, Shu Wang, Xianyu Wu
Summary: In this study, a new multispectral imaging system called CAMSRIS is proposed that achieves multispectral imaging with high temporal and spatial resolutions. The proposed registration algorithm aligns pairs of different view images, while a novel super-resolution, spectral-clustering-based image reconstruction algorithm improves spatial resolution and preserves spectral information. The results demonstrate that CAMSRIS outperforms a multispectral filter array system in terms of spatial and spectral quality and operational efficiency.
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2023)
Article
Geochemistry & Geophysics
Likun Chen, Yanfeng Gu, Xian Li, Xiangrong Zhang, Baisen Liu
Summary: An article proposes a normalized spatial-spectral supervoxel segmentation method for multispectral point cloud (MPC) data, which can segment MPC without the need for any manual annotation and achieves better performance compared to other methods, as demonstrated in experiments.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2023)
Article
Computer Science, Artificial Intelligence
Jie Zhang, Pengpeng Yao, Hochung Wu, John H. Xin
Summary: This paper presents a grid-based algorithm called GDPC for automatically recognizing patterns and extracting colors of multispectral images of printed fabrics. Experimental results demonstrate that the proposed method achieves higher accuracy in recognizing intricate patterns and colors, and requires less computational time.
JOURNAL OF INTELLIGENT MANUFACTURING
(2023)
Article
Remote Sensing
Dilong Li, Xin Shen, Haiyan Guan, Yongtao Yu, Hanyun Wang, Guo Zhang, Jonathan Li, Deren Li
Summary: This paper proposes a point-wise deep learning-based method for land cover classification using airborne multispectral LiDAR data, which efficiently extracts spatial geometric structure features and integrates multi-scale features, achieving effective and efficient performance in land cover classification tasks.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2022)
Article
Optics
Zhongzheng Liu, Shalei Song, Binhui Wang, Wei Gong, Yanhong Ran, Xiaxia Hou, Zhenwei Chen, Faquan Li
Summary: This paper proposes a highlight removal method for multispectral LiDAR (MSL) color point clouds to improve the visual effect of 3D visualization. The method utilizes a reflection model and color information to restore the color of the MSL point clouds, and employs data conversion and color denoising techniques to enhance processing efficiency and recover highlight regions. Experimental evaluation on representative targets demonstrates the effectiveness of the proposed method in generating high-quality highlight-free MSL point clouds.
Article
Environmental Sciences
Brindusa Cristina Budei, Benoit St-Onge, Richard A. A. Fournier, Daniel Kneeshaw
Summary: Identifying tree species using multispectral lidar can improve forest management decision-making, but the influence of scan angle on classification accuracy needs to be evaluated. This study found that the correlation between feature values and scan angle was poor, with minimal impact on species classification accuracy.
Article
Environmental Sciences
Maria Mylonaki, Elina Giannakaki, Alexandros Papayannis, Christina-Anna Papanikolaou, Mika Komppula, Doina Nicolae, Nikolaos Papagiannopoulos, Aldo Amodeo, Holger Baars, Ourania Soupiona
Summary: The automated aerosol type classification method, SCAN, is independent of optical properties and not affected by overlapping values, making it valuable for classifying different aerosol mixtures. Compared to other methods like NATALI and MD, SCAN shows lower percentage of unclassified layers and is capable of classifying aerosol layers based on even single lidar signals.
ATMOSPHERIC CHEMISTRY AND PHYSICS
(2021)
Article
Computer Science, Artificial Intelligence
Bahaeddin Turkoglu, Sait Ali Uymaz, Ersin Kaya
Summary: Clustering analysis is widely used in various fields. In this study, the Artificial Algae Algorithm was used for clustering and compared with ten well-known bio-inspired metaheuristic clustering approaches. The results demonstrate that the AAA clustering method provides more accurate solutions with a higher convergence rate.
INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS
(2022)
Article
Computer Science, Software Engineering
Yousuf Soliman, Albert Chern, Olga Diamanti, Felix Knoeppel, Ulrich Pinkall, Peter Schroeder
Summary: The research presents an efficient algorithm for constructing surfaces with specific constraint conditions, which can be applied to triangle meshes of arbitrary topology.
ACM TRANSACTIONS ON GRAPHICS
(2021)
Article
Nanoscience & Nanotechnology
Yun Huang, Yining Zhu, Bing Qin, Yiwei Zhou, Rui Qin, Pintu Ghosh, Min Qiu, Qiang Li
Summary: Multispectral camouflage is crucial for the safety of facilities, vehicles, and humans, especially in the infrared-microwave range. This research proposes a hierarchical visible-infrared-microwave scattering surface-based scheme for multispectral camouflage, which achieves low infrared radiation, microwave camouflage, and tunable visible color camouflage.
Article
Optics
S. Gandhimathi Alias Usha, S. Vasuki
Summary: The paper proposed a method for time series analysis of multispectral images using hybrid graph cut segmentation and game theory classifier. The approach outperformed traditional algorithms in terms of stability and performance, demonstrating superiority in monitoring changes in the earth's surface information.
Article
Environmental Sciences
Zhuangwei Jing, Haiyan Guan, Peiran Zhao, Dilong Li, Yongtao Yu, Yufu Zang, Hanyun Wang, Jonathan Li
Summary: A novel point-wise multispectral LiDAR point cloud classification architecture, SE-PointNet++, has been proposed in this paper by integrating SE block with an improved PointNet++ network. Experimental results demonstrate that SE-PointNet++ achieves promising performance in multispectral LiDAR point cloud classification tasks.
Article
Chemistry, Analytical
Zizi Chen, Gary W. Small
Summary: A pattern recognition methodology was developed for automated detection of marine oil spills in passive infrared multispectral remote sensing images. By applying classifiers to preprocessed radiances, oil slicks with different thermal contrasts against water were detected. The classification system demonstrated good prediction performance by achieving high overall classification accuracies.
Review
Computer Science, Artificial Intelligence
Absalom E. Ezugwu, Amit K. Shukla, Moyinoluwa B. Agbaje, Olaide N. Oyelade, Adan Jose-Garcia, Jeffery O. Agushaka
Summary: Cluster analysis is essential in data mining, but traditional algorithms requiring a priori knowledge of cluster number may struggle with unknown cluster quantities. Therefore, automatic clustering techniques are indispensable for their flexibility and effectiveness.
NEURAL COMPUTING & APPLICATIONS
(2021)
Article
Environmental Sciences
Yaotao Luo, Donghui Xie, Jianbo Qi, Kun Zhou, Guangjian Yan, Xihan Mu
Summary: LiDAR is a widely used technology for acquiring three-dimensional information about physical objects and environments. A LiDAR simulation model was developed that can accurately simulate LiDAR waveforms and point clouds, and the performance of the simulator was compared with other models. The findings demonstrate that the proposed LiDAR simulator has great potential and offers faster simulation speeds.