An Improved Biologically-Inspired Image Fusion Method
文献类型：期刊论文
| 作者 | Wang, Y. Q.; Wang, Y. |
| 刊名 | International Journal of Pattern Recognition and Artificial Intelligence
 |
| 出版日期 | 2018 |
| 卷号 | 32期号:8页码:20 |
| 关键词 | Image fusion rattlesnake retinex human visual system color-vision ir Computer Science |
| ISSN号 | 0218-0014 |
| DOI | 10.1142/s0218001418570045 |
| 英文摘要 | A biologically inspired image fusion mechanism is analyzed in this paper. A pseudo- color image fusion method is proposed based on the improvement of a traditional method. The proposed model describes the fusion process using several abstract definitions which correspond to the detailed behaviors of neurons. Firstly, the infrared image and visible image are respectively ON against enhanced and OFF against enhanced. Secondly, we feed back the enhanced visible images given by the ON-antagonism system to the active cells in the center-surrounding antagonism receptive field. The fused +VIS+IR signal are obtained by feeding back the OFF-enhanced infrared image to the corresponding surrounding- depressing neurons. Then we feed back the enhanced visible signal from OFF-antagonism system to the depressing cells in the center-surrounding antagonism receptive field. The ON-enhanced infrared image is taken as the input signal of the corresponding active cells in the neurons, then the cell response of infrared-enhance-visible is produced in the process, it is denoted as +IR+VIS. The three kinds of signal are considered as R, G and B components in the output composite image. Finally, some experiments are performed in order to evaluate the performance of the proposed method. The information entropy, average gradient and objective image fusion measure are used to assess the performance of the proposed method objectively. Some traditional digital signal processing-based fusion methods are also evaluated for comparison in the experiments. In this paper, the Quantitative assessment indices show that the proposed fusion model is superior to the classical Waxman's model, and some of its performance is better than the other image fusion methods. |
| 源URL | [http://ir.ciomp.ac.cn/handle/181722/60905]  |
| 专题 | 中国科学院长春光学精密机械与物理研究所 |
| 推荐引用方式 GB/T 7714 | Wang, Y. Q.,Wang, Y.. An Improved Biologically-Inspired Image Fusion Method[J]. International Journal of Pattern Recognition and Artificial Intelligence,2018,32(8):20. |
| APA | Wang, Y. Q.,&Wang, Y..(2018).An Improved Biologically-Inspired Image Fusion Method.International Journal of Pattern Recognition and Artificial Intelligence,32(8),20. |
| MLA | Wang, Y. Q.,et al."An Improved Biologically-Inspired Image Fusion Method".International Journal of Pattern Recognition and Artificial Intelligence 32.8(2018):20. |
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