원문정보
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
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