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The paper introduces FReSH-IR, a lightweight all-in-one weather restoration method that decomposes feature representations into high- and low-frequency components across a hierarchical encoder-decoder. By integrating spectral decomposition with Fourier-based skip connections, it captures complementary frequency information while preserving spatial detail. The approach achieves comparable restoration quality to transformer-based models while using 80% fewer parameters and operations, making it efficient for high-resolution images and constrained-resource systems.
arXiv:2608.28730v1 Announce Type: cross Abstract: Latest JPEG restoration systems achieve strong quality with large models, yet often remain too slow and expensive for efficient on-device deployment....
arXiv:2609.31170v1 Announce Type: new Abstract: Task-driven image restoration aims to improve both image quality and downstream task performance. However, existing methods predominantly focus on sing...
Incorrect exposure degrades both image brightness and recoverable scene detail. Existing sRGB-based correction methods are limited by the non-linear image signal processing pipeline, whereas RAW-based...
arXiv:2610.28191v1 Announce Type: new Abstract: Incorrect exposure degrades both image brightness and recoverable scene detail. Existing sRGB-based correction methods are limited by the non-linear im...
arXiv:2608. 20263v1 Announce Type: new Abstract: We propose UHDformer++, a general Transformer-based framework to solve numerous Ultra-High-Definition (UHD) image restoration tasks.