Earticle

초록

영어

Image fusion is an important branch of information fusion, which is widely used in various fields. At present, the image fusion method is mainly aimed at the different frequency information of the images, the images are fused in transform domain. But in practical application, image fusion is used to improve the credibility of the target information and the demand of background information of is not high. Therefore, this paper puts forward an image fusion method combining with image classification. Firstly, the NSCT transform is used to transform the source images, and the K-Means method is used to realize the classification of the target and the background, and the different fusion criteria are used to get the target and the background. The experimental results show that the image fusion based classification method has a better effect on the subjective visual effect and objective evaluation index.

목차

Abstract
 1. Introduction
 2. K-Means
 3. Introduction of PCNN Theory
 4. Image Fusion Method Based on Image Classification and PCNN
  4.1.Image Classification Based on K-Means in NSCT Domain
  4.2. Background Information Fusion Criterion
  4.3. Target Information Fusion Criterion
 4. Experimental Results and Analysis
 5. Conclusion
 References

키워드

저자

• Jitao Zhang [ Higher Education Key Lab for Measuring & Control Technology and Instrumentations of Heilongjiang, Harbin University of Science and Technology, Harbin, China ]
• Aili Wang [ Higher Education Key Lab for Measuring & Control Technology and Instrumentations of Heilongjiang, Harbin University of Science and Technology, Harbin, China ]
• Jiaying Zhao [ Higher Education Key Lab for Measuring & Control Technology and Instrumentations of Heilongjiang, Harbin University of Science and Technology, Harbin, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605