The paper introduces a unified training framework for underwater image enhancement that addresses the scarcity of paired clean-degraded datasets. It employs a text-guided diffusion model to generate diverse, semantically consistent degraded images and uses a progressive degradation curriculum to balance learning across multiple attributes and difficulty levels. The approach also incorporates a transmission-guided one-step diffusion model to handle varying degradation severity, achieving superior performance on several underwater benchmarks.
By Hongri Tian, Wenxue Li, Tian Ye, Sixiang Chen, Lujia Wang, Xianying Wang, Xinhu Zheng, Gang Hua, Lei Zhu
The paper presents an all-in-one framework for restoring polarization images affected by multiple coupled degradations. It identifies the normalized Stokes representation as effective for separating intensity and polarization, and introduces a dual-branch architecture that uses pretrained general restoration priors for the intensity branch while transferring knowledge to the polarization branch via cross-domain feature transform. A composite-degradation benchmark is also established to support future research.
By Chenggong Li, Jinhao Liu, Caiyun Wu, Yidong Luo, Junchao Zhang, Degui Yang
arXiv:2608. 08965v1 Announce Type: new Abstract: Underwater images often suffer from diverse and coexisting degradations, including color distortion, scattering haze, texture attenuation, and uneven illumination.
By Weifeng Kong, Chenghao Xu, Lin Chen, Ziheng Cao, Guanying Huo
UniPolar is a new framework for restoring images and polarimetric data from color polarization filter array (CPFA) images that suffer from both device- and environment-induced degradations. It uses two complementary streams to reconstruct four polarization-angle images and predict Stokes difference components, coordinating them with a Degradation Conditioned Cross Domain Interaction module that exchanges frequency-selective evidence and applies condition-adaptive feature correction. The method also enforces physical consistency at the output level, aligning image-derived and directly predicted Stokes components while regularizing angular fidelity and the physical feasibility of degree of linear polarization (DoLP).
By Yang Jin, Guangyu Guo, Linghao Shen, Binglu Wang
WaterClear-GS introduces a physics-informed Gaussian splatting method tailored for underwater 3D reconstruction and appearance restoration. It models underwater degradation as intrinsic Gaussian attributes and employs a dual-branch optimization that separates clean appearance from degradation while preserving photometric consistency. The approach incorporates depth-guided geometry regularization, perception-driven supervision, exposure constraints, adaptive regularization, and spectral regularization, achieving strong novel view synthesis and image restoration performance at over 160 FPS.
By Xinrui Zhang, Yufeng Wang, Zesheng Wang, Dacheng Qi, Wenrui Ding, Shuangkang Fang
DPSF-Net is a dual‑prior spatial‑frequency network designed for real‑world remote sensing image dehazing. It combines hazy RGB images with dark channel prior maps as joint inputs, and incorporates a spatial‑frequency residual interaction block, a prior‑guided feature attention module, and a selective kernel complementary fusion module to reduce colour shift, structural distortion, and large‑scale haze. Experiments show that DPSF-Net achieves state‑of‑the‑art performance on the RRSHID benchmark while maintaining a favorable balance of restoration quality, parameter count, and computational complexity.
By Mei Lu, Shangliang Shao, Shanliang Yao
AQUA-Net is a lightweight underwater image enhancement model that fuses spatial, frequency, and illumination information through a residual encoder‑decoder architecture with dual auxiliary branches. The frequency fusion encoder incorporates Fourier‑domain cues to preserve textures and details, while the illumination‑aware decoder applies adaptive exposure correction based on a learned illumination map. Experiments on benchmark datasets and a new high‑resolution Mediterranean Sea video set demonstrate that AQUA-Net achieves state‑of‑the‑art performance with fewer parameters, showing strong generalization and robustness for real‑world underwater imaging.
By Munsif Ali, Najmul Hassan, Lucia Ventura, Davide Di Bari, Simonepietro Canese, Jungpil Shin
Loop‑Mamba is a lightweight, loop‑based state‑space framework designed for restoring old photographs that suffer from multiple degradations such as scratches, cracks, fading, blur, noise, and missing regions. It models restoration as progressive state evolution, using a Semantic‑Guided Degradation Estimator to predict local degradation maps and global scores, and a Shared Structural Memory Mamba to maintain a persistent restoration state across iterations. The method employs first‑order state recursion and a multi‑directional scanning strategy to reduce gradient dilution and computational overhead, and introduces the Old Photo Damage Recovery Score (ODRS) to evaluate both degradation recovery and structural reconstruction, achieving superior performance on the SynOld benchmark.
By Runci Bai, Yucheng Xin, Pu Wang, Yongcong Wang, Chen Wu, Dianjie Lu, Guijuan Zhang, Pengwen Dai, Guangwei Gao, Siyuan Yao, Zhuoran Zheng
arXiv:2608. 09482v1 Announce Type: cross Abstract: All-in-one image restoration is a unified low-level vision task that aims to effectively recover high-quality images from inputs degraded by various types and levels of corruption using a single model.
By Chunxiao Liu, Wei Liu, Anbin Xiong, Erli Meng
Reconstructing photorealistic scenes in unconstrained underwater environments remains challenging due to severe media-induced light scattering and unpredictable dynamic objects. Recent feed-forward vi...
arXiv:2608.00137v3 Announce Type: replace-cross
Abstract: Underwater image enhancement (UIE) aims to recover clear images from observations affected by wavelength-dependent absorption, scattering, an...
By Yifan Chen, Jijun Lu, Ye Zheng, Kaichen Chi, Zhe Sun, Tao Chen
arXiv:2608.22888v1 Announce Type: new
Abstract: Reconstructing photorealistic scenes in unconstrained underwater environments remains challenging due to severe media-induced light scattering and unpr...
By Xiaopeng Guo, Wai Chung Tse, Yipeng Zhu, Hanwen Zhang, Huajian Huang, Sai-Kit Yeung