Earticle

초록

영어

In order to solve storage and computation cost problems for the traditional whole sampling image fusion algorithms, a new method of infrared and visible light image fusion is put forward based on compressed sensing (CS) theory. Nonsubsampled shearlet transform (NSST) is introduced as the sparse transform. Compressed sensing is applied to fuse the high frequency subbands decomposed by NSST. The high frequency coefficients are compressed for measured values which are fused by the rules of spatial frequency weighting. Regional energy together with regional standard deviation guides the fusion of the low frequency subband. Finally, the fused image is gained through inverse NSST. The experimental results show that high-quality fused images can be obtained with only one layer NSST. The fused image quality is better than the several traditional fusion algorithms based on compressed sensing.

목차

Abstract
 1. Introduction
 2. Sparse Transformation
 3. Image Fusion Algorithm Based on NSST and CS
  3.1 Fusion Scheme
  3.2 The Low-Frequency Subband Fusion Rule
  3.3 The High-Frequency Subbands Fusion Rule
 4. Experimental Results
 5. Conclusion
 Acknowledgement
 References

키워드

저자

• WANG Xin [ College of Communication Engineering, Jilin University, Changchun 130022, China ; School of Computer Science& Engineering, Changchun University of Technology, Changchun 130012, China ]
• MENG Jian [ School of Computer Science& Engineering, Changchun University of Technology, Changchun 130012, China ]
• LIU Fu [ College of Communication Engineering, Jilin University, Changchun 130022, China ] Corresponding author

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