Yun Ge
ABSTRACT
The purpose infrared image and visible image fusion work is generating a richer content image. Since these images are captured by two different sensors, the fusion work can merge the valid information into one image. In this paper, we proposed a multi-resolution convolution neural network, which is constructed by multi-scale convolution operators. This method will calculate features in different scales. The multi-scale operators are used to capture multi-features from source images and these feature maps are used to calculate fusion parameter. This can avoid noise and artifact impaction. The fusion results can prove that the multi-fusion method is an effective method.
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Index Terms
- Infrared and visible image fusion using multi-resolution convolution neural network
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