Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1177/1550147717741105 | INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS |
Keywords | Field | DocType |
Image fusion, objects extraction, non-subsampled contourlet transform, multi-sensor data processing, image processing | Computer vision,Pattern recognition,Image fusion,Computer science,Image processing,Fusion,Fusion rules,Sensor fusion,Region growing,Artificial intelligence,Infrared,Contourlet | Journal |
Volume | Issue | ISSN |
13 | 11 | 1550-1477 |
Citations | PageRank | References |
0 | 0.34 | 6 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fanjie Meng | 1 | 23 | 4.93 |
| Ruixia Shi | 2 | 11 | 3.64 |
| Dalong Shan | 3 | 3 | 1.38 |