4 papers
Laplace-Mamba: Laplace Frequency Prior-Guided Mamba-CNN Fusion Network for Image Dehazing
Yongzhen Wang, Liangliang Chen, Bingwen Hu +3
Recent progress in image restoration has underscored Spatial State Models (SSMs) as powerful tools for modeling long-range dependencies, owing to their appealing linear complexity…
M2Restore: Mixture-of-Experts-based Mamba-CNN Fusion Framework for All-in-One Image Restoration
Yongzhen Wang, Yongjun Li, Zhuoran Zheng +2
Natural images are often degraded by complex, composite degradations such as rain, snow, and haze, which adversely impact downstream vision applications. While existing image resto…
WDMamba: When Wavelet Degradation Prior Meets Vision Mamba for Image Dehazing
Jie Sun, Heng Liu, Yongzhen Wang +2
In this paper, we reveal a novel haze-specific wavelet degradation prior observed through wavelet transform analysis, which shows that haze-related information predominantly reside…
WTCL-Dehaze: Rethinking Real-world Image Dehazing via Wavelet Transform and Contrastive Learning
Divine Joseph Appiah, Donghai Guan, Abdul Nasser Kasule +1
Images captured in hazy outdoor conditions often suffer from colour distortion, low contrast, and loss of detail, which impair high-level vision tasks. Single image dehazing is ess…