A Review on Multi-Focus Digital Image Pair Fusion Using Multi-Scale Image Wavelet Decomposition

Authors

  • Priti N. Makode  ME Student, Department of Computer Science and Engineering, G.H. Raisoni College of Engineering & Management, Amravati, Maharashtra, India
  • Juned Khan  Assistant Professor, Department of Computer Science and Engineering, G.H. Raisoni College of Engineering & Management, Amravati, Maharashtra, India

Keywords:

Image Fusion, Wavelet Decomposition Techniques, Quality Assessment, Multi Focus Images

Abstract

The successful fusion of images acquired from different modalities or instruments is of great importance in many applications such as medical imaging microscopic imaging remote sensing computer vision and robotics. Optical imaging cameras suffer from the problem of limited depth-of-field of optical lenses, so it is difficult to get an image with all objects in focus. One way to overcome this problem is by using multi-focus image fusion technique, in which several images with different focus points are combined to form a single image with all objects fully focused. So, it is crucial to effectively extract the image information of the original images and reasonably combine them into the final fusion image. Image fusion is a process of combining relevant information from two or more images into a single informative image. The term image fusion refers to integration of information from different images of same object. The resulting fused output will be more clear and informative than the inputs. This paper proposes an efficient image fusion method based on different Multi-scale image wavelet decomposition techniques. Also quality assessment of fused images analyzes which overcome by our proposed method with better outcomes.

References

  1. Chang-Hwan Son and Xiao-Ping Zhang, “Layer-Based Approach for Image Pair Fusion”, IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 25, NO. 6, JUNE 2016.
  2. Bin Yang and Shutao Li, “Multifocus Image Fusion and Restoration with Sparse Representation” IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, VOL. 59, NO. 4, APRIL 2010.
  3. Mamta Sharma, “A Review : Image Fusion Techniques and Applications”, (IJCSIT) International Journal of Computer Science and Information    Technologies, Vol. 7(3),2016,  1082-1085.
  4. Heng Chu and Weile Zhu, Fusion of IKONOS Satellite Imagery Using IHS Transform and Local Variation, IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, VOL. 5, NO. 4, OCTOBER 2008.
  5. Zelang Miao, Wenzhong Shi, Alim Samat, Gianni Lisini, and Paolo Gamba, Information Fusion for Urban Road Extraction From VHR Optical Satellite Images, IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING.
  6. Shashidhar Sonnad, A Survey on Fusion of Multispectral and Panchromatic Images for High Spatial and Spectral Information This full-text paper was peer-reviewed and accepted to be presented at the IEEE WiSPNET 2016 conference.
  7. Ni-Bin Chang, Kaixu Bai, Sanaz Imen, Chi-Farn Chen, and Wei Gao[7], Multisensor Satellite Image Fusion and Networking for All-Weather Environmental Monitoring, This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination.
  8. Sheng Zheng, Wen-zhong Shi, Jian Liu, and Jinwen Tian[, Remote Sensing Image Fusion Using Multiscale Mapped LS-SVM, IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 46, NO. 5, MAY 2008.
  9. Yashaswini V A, P. Bhuvaneswari, B. Aravind, Multi Model Image Registration and Fusion using Fast Discrete Contour let Transform, International Journal of Advanced   Networking & Applications (IJANA) ISSN: 0975-0282.

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Published

2017-02-28

Issue

Section

Research Articles

How to Cite

[1]
Priti N. Makode, Juned Khan, " A Review on Multi-Focus Digital Image Pair Fusion Using Multi-Scale Image Wavelet Decomposition, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 3, Issue 1, pp.575-579, January-February-2017.