Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Search research articles

Related Experiment Video

Updated: Jan 9, 2026

Measuring the Shape and Size of Activated Sludge Particles Immobilized in Agar with an Open Source Software Pipeline

Measuring the Shape and Size of Activated Sludge Particles Immobilized in Agar with an Open Source Software Pipeline

Published on: January 30, 2019

M2Restore: Mixture-of-Experts-Based Mamba-CNN Fusion Framework for All-in-One Image Restoration.

Yongzhen Wang, Yongjun Li, Zhuoran Zheng

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society

|December 8, 2025

Summary

This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Association of multidisciplinary collaborative nursing with cognitive function and quality of life after craniotomy for glioma resection: a retrospective comparative study.

Frontiers in medicine·2026

Same author

Embodied Spatial Affordance: Spatial-Aware Affordance Learning for Embodied Navigation and Manipulation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026

Same author

Circadian clock and cancer.

Military Medical Research·2026

Same author

Multi-Omics Analysis Reveals m7G Methylation-Related Genes May Be Involved in TGF-β Signaling-Mediated Anti-PD-L1 Response in Bladder Cancer.

ImmunoTargets and therapy·2026

Same author

MonoRelief V2: Leveraging Real Data for High-Fidelity Monocular Relief Recovery.

IEEE transactions on visualization and computer graphics·2026

Same author

CoreEditor: Correspondence-Constrained Diffusion for Consistent 3D Editing.

IEEE transactions on visualization and computer graphics·2026

Same journal

Change-Prior-Guided Unsupervised Change Detection of Heterogeneous Remote Sensing Images.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026

Same journal

AgonicDreamer: Enhancing Multi-View Consistency in Text-to-3D Generation via Rectified Score Distillation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026

Same journal

BiCM-Prompt: Bidirectional Cross-Modal Prompt Tuning for Class-Incremental Learning on Multisource Remote Sensing Images.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026

Same journal

GoP-based Quality Enhancement on Video Compression.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026

Same journal

Align then Tensorize: Multi-Level Consistent Anchor Graph Learning for Scalable Multi-View Clustering.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026

Same journal

Beyond Fidelity: Diverse Image Synthesis via Retrieval-Augmented Diffusion.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026

See all related articles

M2Restore, a novel framework, enhances image restoration by combining Mixture-of-Experts (MoE) and Mamba-CNN models. It achieves superior generalization and detail preservation across diverse degradations like rain, snow, and haze.

Area of Science:

Computer Vision
Image Processing
Deep Learning

Background:

Natural images suffer from composite degradations (rain, snow, haze), impacting vision tasks.
Existing image restoration methods struggle with generalization and balancing local details with global context.

Purpose of the Study:

To introduce M2Restore, an efficient and robust all-in-one image restoration framework.
To address the limitations of current methods in handling diverse degradations and preserving image fidelity.

Main Methods:

Developed a Mixture-of-Experts (MoE)-based Mamba-CNN fusion framework.
Implemented a CLIP-guided MoE gating mechanism with cross-modal feature calibration for expert selection.
Designed a dual-stream architecture integrating CNNs and Mamba for joint global and local feature modeling.

Related Experiment Videos

Last Updated: Jan 9, 2026

Measuring the Shape and Size of Activated Sludge Particles Immobilized in Agar with an Open Source Software Pipeline

Measuring the Shape and Size of Activated Sludge Particles Immobilized in Agar with an Open Source Software Pipeline

Published on: January 30, 2019

Introduced an edge-aware dynamic gating mechanism for adaptive attention allocation.

Main Results:

M2Restore demonstrates superior generalization across various degradation conditions.
The framework effectively balances global context modeling and fine-grained local detail preservation.
Achieved state-of-the-art performance in visual quality and quantitative metrics on multiple benchmarks.

Conclusions:

M2Restore offers an efficient and robust solution for all-in-one image restoration.
The proposed fusion framework and gating mechanisms significantly improve restoration quality and adaptability.
The approach provides a promising direction for future research in complex image degradation scenarios.