Multi-sensor image fusion based on regional characteristics
Multi-sensor data fusion method has been widely investigated in recent years. This article presents a novel fusion algorithm based on regional characteristics for combining infrared and visible light images in order to achieve an image with clear objects and high-resolution scene. First, infrared ob...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2017-11-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/1550147717741105 |
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| Summary: | Multi-sensor data fusion method has been widely investigated in recent years. This article presents a novel fusion algorithm based on regional characteristics for combining infrared and visible light images in order to achieve an image with clear objects and high-resolution scene. First, infrared objects are extracted by region growing and guided filter. Second, the whole scene is divided into the objects region, the smooth region, and the texture region according to different regional characteristics. Third, the non-subsampled contourlet transform is used on infrared and visible images. Then, different fusion rules are applied to different regions, respectively. Finally, the fused image is constructed by the inverse non-subsampled contourlet transform with all coefficients. Experimental results demonstrate that the proposed objects extraction algorithm and the fusion algorithm have good performance in objective and subjective assessments. |
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| ISSN: | 1550-1477 |