Earticle

초록

영어

Faced with the poor ability of traditional transform domain tools to capture the image information and the high requirements on the precision and real-time of medical imaging, a novel fusion technique for medical images based on shearlet transform (ST) and compressive sensing (CS) model is proposed in this paper. Due to the better competence of image information capturing, ST is utilized to conduct the multi-scale and multi-directional decompositions of source images. In addition, the measurement matrix is adopted to realize the sparse representation of the high-frequency coefficients obtained from ST. The fusion data of high-frequency sub-images can be attained via the largest-value method. Finally, the final fused image can be obtained by using inverse ST. Compared with current typical techniques especially the non-negative matrix factorization based ones; simulation experimental demonstrates that the proposed one has remarked superiorities in terms of both subjective and objective evaluations.

목차

Abstract
 1. Introduction
 2. Basic Theories
  2.1. ST Basic Model [8-10]
  2.2. Basic Compressive Sensing Model [11, 12]
 3. Medical image Fusion based on ST and CS Model
  3.1. Image Fusion Basic Model
  3.2. Low-frequency Microcosmic Subband Image Fusion
  3.3. High-frequency microcosmic subband image fusion
 4. Experimental Results and Analysis
  4.1. Experiments Introduction
  4.2. Experimental Results and Analysis
 5. Conclusion
 Acknowledgments
 References

키워드

저자

• Niu Ling [ Zhou Kou Normal University, Zhoukou 466001, China ]
• Duan Mei-Xia [ North China University of Water Resources and Electric Power, Zhenzhou 450011, 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