Dual-Region Search Detection
Published:
An Infrared Small Moving Target Detection Method Based on Dual-Region Search in Complex Scenes
H Cao, Y Hu, Z Wang, J Yang, G Zhou, W Wang, Y Liu
Published in Remote Sensing, January 2025
DOI
Project Overview
Challenge: Target Diversity
Complex scenes contain diverse target types:
- Fast moving jets
- Slow hovering drones
- Boats with wake patterns
- Ground vehicles with different signatures
Single strategy cannot handle all types effectively.
Solution: Dual-Region Strategy
Adaptive search based on target characteristics:
- Region A: Fast targets, simple backgrounds
- Region B: Complex backgrounds, dim targets
- Dynamic allocation: Automatic region selection
Key Innovations
1. Automatic Region Classification
Scene analysis:
- Background complexity estimation
- Target motion prediction
- Automatic region assignment
2. Specialized Detectors
Region A detector:
- Optimized for speed
- Motion-based detection
- Low computational cost
Region B detector:
- Deep analysis capability
- Background suppression
- High sensitivity
3. Intelligent Fusion
Decision-level fusion:
- Combine results from both regions
- Resolve conflicts intelligently
- Optimize overall performance
Method
System Architecture
Input Image
↓
[Scene Analysis Module]
├── Background complexity
├── Target characteristics
└── Region assignment
↓
[Parallel Detection]
├── Region A Detector (fast)
└── Region B Detector (deep)
↓
[Result Fusion]
├── Conflict resolution
├── Confidence weighting
└── Final output
Results
Comprehensive evaluation on diverse datasets:
- Handles 5+ target categories
- Adapts to 10+ scene types
- Superior to single-strategy methods
Applications
- Multi-threat detection: Various aerial targets
- Maritime surveillance: Ships, boats, swimmers
- Traffic monitoring: Mixed vehicle types
- Urban security: Complex city environments
Citation
@article{cao2025dual,
title={An Infrared Small Moving Target Detection Method in Complex Scenes Based on Dual-Region Search},
author={Cao, H and Hu, Y and Wang, Z and Yang, J and Zhou, G and Wang, W and Liu, Y},
journal={Remote Sensing},
volume={17},
number={2},
pages={323},
year={2025},
publisher={MDPI}
}
