Deep Learning for In-Orbit Cloud Segmentation and Classification in Hyperspectral Satellite Data

arXiv:2403.08695v1 Announce Type: new
Abstract: This article explores the latest Convolutional Neural Networks (CNNs) for cloud detection aboard hyperspectral satellites. The performance of the latest 1D CNN (1D-Justo-LiuNet) and two recent 2D CNNs (nnU-net and 2D-Justo-UNet-Simple) for cloud segmentation and classification is assessed. Evaluation criteria include precision and computational efficiency for in-orbit deployment. Experiments utilize NASA's EO-1 Hyperion data, with varying spectral channel numbers after Principal Component Analysis. Results indicate that 1D-Justo-LiuNet achieves the highest accuracy, outperforming 2D CNNs, while …

abstract article arxiv classification cloud cnn cnns convolutional neural networks cs.cv data deep learning detection eess.iv evaluation networks neural networks performance precision satellite satellites segmentation simple type unet