SavedAdd your journal

Journals / Electronic Letters on Science and Engineering / 2017 / Cilt: 13 - Sayı: 3

Multi-Focus Image Fusion Based on Shearlet Transform Using Genetic Algorithm

Harun Akbulut
Veysel ASLANTAS
Hasan ULUTAŞ
Pages
10–16
Publication Date
2017-12-31
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Experimental results show that the proposed method is more effectively than traditional method.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this paper, a novel method for multi focus image fusion based on shearlet transform using genetic algorithm is proposed.
📊
Key Findings & Data:First of all, ST is firstly applied to source images separately.
💡
Conclusion & Impact:Experimental results show that the proposed method is more effectively than traditional method.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Genetic Algorithm · Multi-Focus Image Fusion · Shearlet Transform

Abstract

In this paper, a novel method for multi focus image fusion based on shearlet transform using genetic algorithm is proposed. Proposed method consist of three basic steps. First of all, ST is firstly applied to source images separately. Then, fusion rate of source images is determined using GA and source images are fused according to the rate of fusion determined by GA. Lastly, fused image is obtained applying inverse ST to fused image of ST. Fused image is evaluated according to quality metrics such as variance, spatial frequency. Experimental results show that the proposed method is more effectively than traditional method. Together with GA and ST for multi focus image fusion is firstly presented in literature.

🔖

Cite This Article

Akbulut, H., ASLANTAS, V., ULUTAŞ, H. (2017). Multi-Focus Image Fusion Based on Shearlet Transform Using Genetic Algorithm. Electronic Letters on Science and Engineering, Cilt: 13 - Sayı: 3, 10–16. https://ajindex.com/articles/133661

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (7)

  1. V. Aslantaş, R. Kurban, "Fusion of multi-focus images using differential evolution algorithm", Expert Systems with Applications, Volume 37, Issue 12, December 2010, Pages 8861-8870
  2. R. Kurban, “Resim Uzayında Blok Seçmeye Dayalı Yeni Görüntü Birleştirme Yöntemleri”, Doktora Tezi, Erciyes Üniversitesi, Kayseri, 2012
  3. K. Guo, D. Labate, “Optimally sparse multi-dimensional representation using shearlet”, SIAM Journal of Mathematical Analysis and Application 39, 2007, pp. 298-318
  4. Y. Cao, S. Li and J. Hu, “Multi-Focus Image Fusion by Nonsubsampled Shearlet Transform”, Sixth International Conference on Image and Graphics, China,2011
  5. L. Lü, J. Zhao and H. Sun, “Multi-Focus Image Fusion Based on Shearlet and Local Energy”, 2nd International Conference on Signal Processing Systems, China, 2010
  6. H. Wang, Y. Liu and Shupeng Xu, “An Image Fusion Algorithm Based on Shearlet”, Third International Conference on Information Science and Technology, March 23-25, 2013; Yangzhou, Jiangsu, China
  7. Aslantas V., "A singular-value decomposition-based image watermarking using genetic algorithm", Int. J. Electron. Commun. (AEÜ) 62 (2008) 386 – 394, 2007.