Earticle

초록

영어

Aiming at the problems that the luminance information is not enough and the edge information can not be preserved easily in the process of the image fusion, an effective image fusion method based on nonsubsampled contourlet transform (NSCT) and adaptive guided image filtering is proposed in this paper. Firstly the source images are decomposed by NSCT with multi-scale, multi-direction and shift-invariant properties. The fusion rule of the low-frequency subband coefficients employs the local correlation energy to improve the energy and information of the subband coefficients. To acquire good effects with edge-preserving and noise reduction, the adaptive guided image filtering is introduced to the high-frequency subband coefficients as the fusion rule for the first time, and it can make use of halo-free edge slope enhancement in the fusion process. Finally, the fused image is reconstructed by the inverse NSCT. Experimental results demonstrate that the comprehensive performances of the proposed method are improved in the fusion information, edge and luminance.

목차

Abstract
 1. Introduction
 2. NSCT
 3. Guided Image Filtering
 4. The Proposed Method and Its Fusion Rules
  4.1. General Framework for the Proposed Method
  4.2. Low Frequency Fusion Rule
  4.3. High Frequency Fusion Rule
 5. Experimental Results and Analysis
  5.1. The Experimental Results
  5.2. The Evaluation Indexes
 6. Conclusions
 References

키워드

저자

• Zhenbing Zhao [ North China Electric Power University, School of Electrical and Electronic Engineering, Hebei, China ]
• Yinping Cai [ North China Electric Power University, School of Electrical and Electronic Engineering, Hebei, China ] Corresponding Author
• Yincheng Qi [ North China Electric Power University, School of Electrical and Electronic Engineering, Hebei, China ]
• Ning Liu [ North China Electric Power University, School of Electrical and Electronic Engineering, Hebei, 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