Earticle

초록

영어

Aiming at solving the fusion problem of multimodal medical images, a novel medical image fusion algorithm is present in this paper. The multiwavelet is combined with the NSDFB to construct the proposed Multi-NSDFB transform. The source images can be decomposed into several lowpass coefficient and highpass coefficient. And all coefficients can be decomposed into four direction subbands. The modified spatial frequency is adopted to motivate the pulse coupled neural network to select the every direction subbands coefficients. Experiment results demonstrate that the proposed algorithm can not only extract more important visual information from source images, but also effectively avoid the introduction of artificial information. The present scheme outperforms the redundant discrete wavelet transform-based, and the Ripplet transform-based in terms of both visual quality and objective evaluation.

목차

Abstract
 1. Introduction
 2. Multi-NSDFB Transform
  2.1. Multiwavelet
  2.2. NSDFB
  2.3. The Multi-NSDFB Transform
 3. Fusion Rule
  3.1. Modified Spatial Frequency
  3.2. PCNN
 4. Proposed Method
 5. Experimental Results and Analysis
 6. Conclusion
 References

키워드

저자

• Peng Geng [ School of Information Science and Technology, Shijiazhuang Tiedao University, Shijiazhuang, China ]
• Xing Su [ School of Information Science and Technology, Shijiazhuang Tiedao University, Shijiazhuang, China ]
• Tan Xu [ Department of Physics and Electronic Information, Hengshui University, Hengshui, China ]
• Jianshu Liu [ Shijiazhuang Appraisal Center of Vocation Skill and Teaching Research, Shijiazhuang, 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