PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
November 25, 2025IEEE Transactions on Image Processing

NDMamba: Dual-Prior State-Space Model for Nighttime Deraining

View Full Paper
Ask AI
Bookmark
Share

Authors

ZLZhi-Rui LiuSSShangquan SunCLChaopeng Li

Discussion

Loading...

Member takes

Overview

The new state-space model improves nighttime image deraining using convolutional neural networks, suggesting better light and rain modeling for efficiency.

Key Points

  • Dual-prior state-space model enhances deraining performance in low-light conditions, and improves efficiency through advanced architecture.
  • Key experiments verified that the state-space model outperformed existing techniques on various benchmark datasets for deraining.
  • The approach integrates convolutional neural networks to model both lighting and rain influences effectively during nighttime.
  • This development may lead to better image restoration in practical nighttime conditions, necessitating future evaluations on real-world scenarios.

Cite This Study

Liu et al. (2025) studied this question.

synapsesocial.com/papers/692502b787af00ed34ac2048https://doi.org/10.1109/tip.2025.3633561
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1RainMamba: Enhanced Locality Learning with State Space Models for Video Deraining2024 · 12 citations
  2. 2DWMamba: a structure-aware adaptive state space network for image quality improvement2025
  3. 3MambaDPF-Net: A Dual-Path Fusion Network with Selective State Space Modeling for Robust Low-Light Image Enhancement2025
  4. 4Visual State Space Model for Image Deraining with Symmetrical Scanning2024 · 4 citations
  5. 5SFQMamba: A Spatial–Frequency Deraining Framework for Robust Visual Sensing in UAV-Assisted IoT Systems2026