中国物理B ›› 2018, Vol. 27 ›› Issue (11): 118706-118706.doi: 10.1088/1674-1056/27/11/118706
所属专题： SPECIAL TOPIC — 80th Anniversary of Northwestern Polytechnical University (NPU)
• SPECIAL TOPIC—Recent advances in thermoelectric materials and devices • 上一篇 下一篇
An infrared and visible image fusion method based uponmulti-scale and top-hat transforms
Gui-Qing He(何贵青), Qi-Qi Zhang(张琪琦), Jia-Qi Ji(纪佳琪), Dan-Dan Dong(董丹丹), Hai-Xi Zhang(张海曦), Jun Wang(王珺)
- 1 School of Electronics and Information, Northwestern Polytechnical University, Xi'an 710072, China;
2 School of Information Technology, Northwestern University, Xi'an 710072, China
An infrared and visible image fusion method based uponmulti-scale and top-hat transforms
Gui-Qing He(何贵青)1, Qi-Qi Zhang(张琪琦)1, Jia-Qi Ji(纪佳琪)1, Dan-Dan Dong(董丹丹)1, Hai-Xi Zhang(张海曦)1, Jun Wang(王珺)2
- 1 School of Electronics and Information, Northwestern Polytechnical University, Xi'an 710072, China;
2 School of Information Technology, Northwestern University, Xi'an 710072, China
摘要：
The high-frequency components in the traditional multi-scale transform method are approximately sparse, which can represent different information of the details. But in the low-frequency component, the coefficients around the zero value are very few, so we cannot sparsely represent low-frequency image information. The low-frequency component contains the main energy of the image and depicts the profile of the image. Direct fusion of the low-frequency component will not be conducive to obtain highly accurate fusion result. Therefore, this paper presents an infrared and visible image fusion method combining the multi-scale and top-hat transforms. On one hand, the new top-hat-transform can effectively extract the salient features of the low-frequency component. On the other hand, the multi-scale transform can extract high-frequency detailed information in multiple scales and from diverse directions. The combination of the two methods is conducive to the acquisition of more characteristics and more accurate fusion results. Among them, for the low-frequency component, a new type of top-hat transform is used to extract low-frequency features, and then different fusion rules are applied to fuse the low-frequency features and low-frequency background; for high-frequency components, the product of characteristics method is used to integrate the detailed information in high-frequency. Experimental results show that the proposed algorithm can obtain more detailed information and clearer infrared target fusion results than the traditional multi-scale transform methods. Compared with the state-of-the-art fusion methods based on sparse representation, the proposed algorithm is simple and efficacious, and the time consumption is significantly reduced.
中图分类号:
- 87.50.W-