ICIP 2024
We’re very excited to announce that our paper, “On The Cloud Detection From Backscattered Images Generated From A Lidar-Based Ceilometer: Current State And Opportunities” has been accepted at the 2024 IEEE International Conference on Image Processing (ICIP 2024), which will be held in Abu Dhabi from October 27 to October 30.
In this paper, we present a new dataset obtained by measurements taken from particular instruments, the ceilometers. A ceilometer is a lidar-based device allowing to analyse the atmosphere and detect the presence of particles within clouds. The data retrieved from ceilometers involve analysis of the backscatter of the lidar signal returning to the surface. Given the inherent noise in this data, we leverage deep learning models to detect the presence of clouds in the data. To label the data, we take advantage of a Weather Research & Forecasating (WRF) model, which provided us with ground-truth used for validation purposes. We performed a comparative analysis with current state-of-the-art deep learning architectures. This comparative analysis shows that the best model is ResNet 50, but also a transformer-based model, such as ViT, achieves great results. These preliminary results pave the scenario for future works aimed at detecting other particles composing the atmosphere, such as polluting agents that can be detected from the ceilometer backscatter data.
Arxiv preprint will be public as soon as possible.
GitHub code repository: https://github.com/alessiochisari/CeilometerDatasetBenchmark
Dataset: https://zenodo.org/records/10616434
Authors: Alessio Barbaro Chisari, Alessandro Ortis, Luca Guarnera, Wladimiro Carlo Patatu, Rosaria Ausilia Giandolfo, Emanuele Spampinato, Sebastiano Battiato, Mario Valerio Giuffrida