Earticle

초록

영어

Combined with the shared similarity among multiple source images and depth of field in a camera, a new image fusion algorithm based on nonsubsampled shearlet transform (NSST) domain is proposed. First, NSST is utilized for decomposition of the source images, the low frequency coefficients is fused by weight votes in the structure-driven regions by using shared similarity and depth of field (SSSID), and then apply larger sum-modified-Laplacian (SML) with depth of field to the high frequency coefficients, finally the fusion image is gained after we do the inverse NSST to the fused coefficients. The algorithm can not only preserve the information of the source images well, but also suppress pixel distortion due to nonlinear operations in transform domain. Experimental results demonstrate that the proposed method outperforms the state-of-the-art transform domain fusion methods on image quality and objective fusion criteria.

목차

Abstract
 1. Introduction
 2. Non-Subsampled Shearlet Transform
 3. Shared Similarity Regions and Depth Information
 4. Image Fusion based on SSSID
 5. Experimental Results
 6. Conclusions
 References

키워드

저자

• Liu Shuaiqi [ Hebei University, College of Electronic and Information Engineering, Baoding, China, Key Laboratory of Digital Medical Engineering of Hebei Province, Baoding, China ]
• Zhu Zhihui [ Colorado School of Mines, Department of Electrical Engineering and Computer Science, Colorado, USA ]
• Li Huiya [ Hebei University, College of Electronic and Information Engineering, Baoding, China, Key Laboratory of Digital Medical Engineering of Hebei Province, Baoding, China ] Corresponding Author
• Zhao Jie [ Hebei University, College of Electronic and Information Engineering, Baoding, China, Key Laboratory of Digital Medical Engineering of Hebei Province, Baoding, China ]
• Wen Xin [ Hebei University, College of Electronic and Information Engineering, Baoding, China, Key Laboratory of Digital Medical Engineering of Hebei Province, Baoding, 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