16 citations · 32 across the 8 of their papers we have counts for
10 papers
Monotone Piecewise-Linear Harmonization of Multitemporal Multispectral Surface Reflectance With Unsupervised Deep Multiview Pseudoinvariant Features Learning
Lino Garda Denaro, Chia-Hsiang Lin
Surface reflectance products derived from optical satellite may exhibit systematic inconsistencies across acquisition dates, because atmospheric correction is generally performed i…
Interpretable Landsat-to-Hyperspectral Dual Super-Resolution Without Large Matrix Inversion
Chia-Hsiang Lin, Jian-Kai Huang, Si-Sheng Young +1
Direct acquisition of global hyperspectral images (HSIs) is infeasible given contemporary hardware facilities and limited resources, while global hyperspectral monitoring is critic…
Anti-Hyperspectral Anomaly Detection: A First Study on Stealthy Lipschitz-Forcing Perturbations Against Unknown Detectors
Chia-Hsiang Lin, Si-Sheng Young, Jon Atli Benediktsson
Hyperspectral imagery represents the best contemporary technology to remotely detect anomalous objects. Nevertheless, hyperspectral anomaly detection (HAD) technique makes ground f…
Underdetermined Blind Source Separation via Weighted Simplex Shrinkage Regularization and Quantum Deep Image Prior
Chia-Hsiang Lin, Si-Sheng Young
As most optical satellites remotely acquire multispectral images (MSIs) with limited spatial resolution, multispectral unmixing (MU) becomes a critical signal processing technology…
Spectral Super-Resolution via Adversarial Unfolding and Data-Driven Spectrum Regularization: From Multispectral Satellite Data to NASA Hyperspectral Image
Si-Sheng Young, Chia-Hsiang Lin
The European Space Agency's Sentinel-2 satellite provides global multispectral coverage for remote sensing (RS) applications. However, limited spectral resolution (12 bands) and no…
HyperKING: Quantum-Classical Generative Adversarial Networks for Hyperspectral Image Restoration
Chia-Hsiang Lin, Si-Sheng Young
Quantum machine intelligence starts showing its impact on satellite remote sensing (SRS). Also, recent literature exhibits that quantum generative intelligences encompass superior…
A Quantum-Empowered SPEI Drought Forecasting Algorithm Using Spatially-Aware Mamba Network
Po-Wei Tang, Chia-Hsiang Lin, Jian-Kai Huang +1
Due to the intensifying impacts of extreme climate changes, drought forecasting (DF), which aims to predict droughts from historical meteorological data, has become increasingly cr…
Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping
Chia-Hsiang Lin, Po-Wei Tang, Alfredo R. Huete
A mangrove mapping (MM) algorithm is an essential classification tool for environmental monitoring. The recent literature shows that compared with other index-based MM methods that…
Transformer-Driven Inverse Problem Transform for Fast Blind Hyperspectral Image Dehazing
Po-Wei Tang, Chia-Hsiang Lin, Yangrui Liu
Hyperspectral dehazing (HyDHZ) has become a crucial signal processing technology to facilitate the subsequent identification and classification tasks, as the airborne visible/infra…
Quantum Information-Empowered Graph Neural Network for Hyperspectral Change Detection
Chia-Hsiang Lin, Tzu-Hsuan Lin, Jocelyn Chanussot
Change detection (CD) is a critical remote sensing technique for identifying changes in the Earth's surface over time. The outstanding substance identifiability of hyperspectral im…