Multi-sensor image fusion based on contrast and directional features optimization
Multi-sensor image fusion is always an important and opening problem, which can enhance visual quality and benefit some social security applications. In this article, we use contrast pyramid to decompose visible and infrared images, respectively, and the directional filter banks are applied to obtai...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2018-12-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/1550147718815841 |
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| Summary: | Multi-sensor image fusion is always an important and opening problem, which can enhance visual quality and benefit some social security applications. In this article, we use contrast pyramid to decompose visible and infrared images, respectively, and the directional filter banks are applied to obtain multiple directional sub-band image features. Then, we compute the decomposition coefficients of visible and infrared images using a low-pass filter on the decomposed data; and finally, we introduce the whale optimization algorithm to search optimal coefficients to reconstruct the final fusion image. The experiments are conducted on multiple datasets with subjective and objective comparisons, in which the qualitative and quantitative analyses indicate the validity of the proposed method. |
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| ISSN: | 1550-1477 |