Multikernel Graph Structure Learning for Multispectral Point Cloud Classification

• Published in: IEEE journal of selected topics in applied earth observations and remote sensing Vol. 17; pp. 5637 - 5650
• Main Authors: Wang, Qingwang, Zhang, Zifeng, Huang, Jiangbo, Shen, Tao, Gu, Yanfeng
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Classification; Convolutional neural networks; Distribution; Graph neural networks; Graph structure learning; Hilbert space; Information processing; Kernel; Land cover; Land surface; Learning; multiple kernel learning; multispectral LiDAR data; Neural networks; Optimization; Performance enhancement; point cloud classification; Point cloud compression; prior constraint; Remote sensing; Three-dimensional displays

Multispectral point cloud, with spatial and multiple-band spectral information, provides the data basis for finer land cover 3-D classification. However, spectral information is not well utilized by traditional methods of point cloud classification. Benefiting from the excellent performance of graph...