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Fusion of Infrared and Visible Images Using Fast Global Smoothing Decomposition and Target-Enhanced Parallel Gaussian
Chaowei Duan1, Changda Xing1,2, Yiliu Liu1
1College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China.
Sensors (Basel, Switzerland)
|January 11, 2022
Summary
This study introduces an efficient infrared (IR) and visible image fusion method. The technique enhances targets while preserving background details, outperforming existing methods in tests.
Area of Science:
- Computer Vision
- Image Processing
- Artificial Intelligence
Background:
- Infrared (IR) and visible image fusion is crucial for applications like surveillance and target detection.
- Existing fusion methods often struggle to simultaneously enhance targets and preserve background details.
Purpose of the Study:
- To propose an efficient IR and visible image fusion method.
- To enhance significant targets/regions while preserving rich background details.
Main Methods:
- Multi-scale representation using a fast global smoother to decompose images into base and detail layers.
- A target-enhanced parallel Gaussian fuzzy logic-based fusion rule for merging base layers.
- A visual saliency map-based fusion rule for merging detail layers.
Main Results:
- The proposed method effectively enhances significant targets and regions.
- Rich background details from visible images are well-preserved.
- Experimental results on multiple image pairs and sequences demonstrate superior performance compared to state-of-the-art methods.
Conclusions:
- The developed fusion method offers a significant improvement over existing techniques.
- The approach is effective for various applications requiring high-quality fused images.
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