Earticle

초록

영어

Image fusion is an important branch of information fusion, widely used in various fields, especially in medical field. So increasing the quality and efficiency of medical image fusion has great significance. Combining the advantages of pulse coupled neural networks with Compressive Sensing; this paper puts forward a novel image fusion method in NSCT transform domain. First, NSCT transform is applied to the source images, and the coefficients in low frequency coefficient are fused by mean rules. For high frequency coefficient, CS is applied and PCNN. Finally, inverse NSCT is applied to get the reconstructed image. The experimental results show that the fusion algorithm proposed in this paper in the performance and integration efficiency has better fusion results.

목차

Abstract
 1. Introduction
 2. Principles of CS
 3. Basic Theory of PCNN
 4. Medical Image Fusion based on Compressive Sensing and Pulse Coupled Neural Network
  4.1 Fusion of Low Frequency Subband Coefficients
  4.2 Fusion of High Frequency Subband Coefficients
 5. Experiments and Results Analysis
 6. Conclusion
 References

키워드

저자

• AiliWang [ Higher Education Key Lab for Measuring & Control Technology and Instrumentations of Heilongjiang, Harbin, China ]
• Jiaying Zhao [ Higher Education Key Lab for Measuring & Control Technology and Instrumentations of Heilongjiang, Harbin, China ]
• Shiyu Dai [ Higher Education Key Lab for Measuring & Control Technology and Instrumentations of Heilongjiang, Harbin, China ]
• Yuji Iwahori [ Dept. of Computer Science, Chubu University, Japan ]
• Yangyang Zhao [ Dept. of Computer Science, Chubu University, Japan ]

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