An Enhanced Geometric-Spectral Feature Learning Framework for Airborne Multispectral Point Cloud Classification
The framework enhances airborne multispectral point cloud classification by using a lightweight encoder-decoder network with two parallel streams for feature extraction. It combines position encoding and spectral guidance to capture complex geometric and spectral information simultaneously, leading to superior performance on mangrove datasets.