Unsupervised Band Selection Using Fused HSI and LiDAR Attention Integrating With Autoencoder

arXiv:2404.05258v1 Announce Type: new
Abstract: Band selection in hyperspectral imaging (HSI) is critical for optimising data processing and enhancing analytical accuracy. Traditional approaches have predominantly concentrated on analysing spectral and pixel characteristics within individual bands independently. These approaches overlook the potential benefits of integrating multiple data sources, such as Light Detection and Ranging (LiDAR), and is further challenged by the limited availability of labeled data in HSI processing, which represents a significant obstacle. To address these challenges, this paper introduces …

abstract accuracy arxiv attention autoencoder benefits cs.cv data data processing data sources imaging lidar multiple pixel processing type unsupervised