Task-Guided Prompting for Unified Remote Sensing Image Restoration
Remote sensing image restoration (RSIR) is essential for recovering high-fidelity imagery from degraded observations, enabling accurate downstream analysis. However, most existing methods focus on single degradation types within homogeneous data, restricting their practicality in real-world scenarios where multiple degradations often across diverse spectral bands or sensor modalities, creating a significant operational bottleneck. To address this fundamental gap, we propose TGPNet, a unified framework capable of handling denoising, cloud removal, shadow removal, deblurring, and SAR despeckling within a single, unified architecture. The core of our framework is a novel Task-Guided Promptin...
| Authors | Wenli Huang, Yang Wu, Xiaomeng Xin et al. |
|---|---|
| Primary category | eess.IV |
| Published | 3 April 2026 |
| Last updated at source | 3 April 2026 |
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