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A Survey on Image Fusion Techniques for Image Enhancement in Digital Image Processing

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2018
Authors:
Rajvinder Kaur, Rupinder Kaur
10.5120/ijca2018917133

Rajvinder Kaur and Rupinder Kaur. A Survey on Image Fusion Techniques for Image Enhancement in Digital Image Processing. International Journal of Computer Applications 179(45):24-27, May 2018. BibTeX

@article{10.5120/ijca2018917133,
	author = {Rajvinder Kaur and Rupinder Kaur},
	title = {A Survey on Image Fusion Techniques for Image Enhancement in Digital Image Processing},
	journal = {International Journal of Computer Applications},
	issue_date = {May 2018},
	volume = {179},
	number = {45},
	month = {May},
	year = {2018},
	issn = {0975-8887},
	pages = {24-27},
	numpages = {4},
	url = {http://www.ijcaonline.org/archives/volume179/number45/29437-2018917133},
	doi = {10.5120/ijca2018917133},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Image fusion procedure is helpful to attain a single output image that contains required data or information by merging two distorted input images. Image fusion is done by pulling out all the necessary information from two images or more than two images after which the extorted information is combined into a distinct fused image. This fused image has improved superiority as compare to the input images. Image fusion is prepared by implementing particular techniques. Those particular schemes for image fusion are introduced in this paper. This paper offers an overview to the work that has been done by in past.

References

  1. Mozhdeh Haddadpour, Sabalan Daneshvar, Hadi Seyedarabi, “PET and MRI image fusion based on combination of 2-D Hilbert transform and IHS method”, Biomedical Journal, Volume 40, Issue 4, Pp 219-225, 2017.
  2. Cheng-I Chen, “Fusion of PET and MR Brain Images Based on IHS and Log-Gabor Transforms”, IEEE Sensors Journal, Volume: 17, Issue: 21, Pp 6995 – 7010, 2017
  3. Mehdi Sefidgar Dilmaghani; Sabalan Daneshvar; Mehdy Dousty, “A new MRI and PET image fusion algorithm based on BEMD and HIS methods”, (ICEE), Pp 118-121, 2017
  4. Behzad Kalafje Nobariyan; Sabalan Daneshvar; Mehdi Hosseinzadeh, “Fusion of SPECT and MRI images using back and fore ground information”, (MVIP), Pp 227-231, 2013
  5. Maruturi Haribabu; Ch. Hima Bindu; K. Satya Prasad, “Multimodal Medical Image Fusion of MRI-PET Using Wavelet Transform”, International Conference on Advances in Mobile Network, Communication and Its Applications, Pp 127 – 130, 2012
  6. Changtao He, Quanxi Liu, Hongliang Li, Haixu Wang, “Multimodal medical image fusion based on IHS and PCA”, Procedia Engineering, Volume 7, Pp 280-285 , 2010. 
  7. Te-Ming Tu, Shun-Chi Su, Hsuen-Chyun Shyu, Ping S. Huan,“A new look at HIS like image fusion methods”,Information Fusion, Volume 2, Issue 3, Pp 177-186, 2001.
  8. Sabalan Daneshvar, Hassan Ghassemian, “MRI and PET image fusion by combining IHS and retina-inspired models”, Information Fusion, Volume 11, Issue 2, Pp 114-123, 2010.
  9. Meenu Manchanda, Rajiv Sharma, “A novel method of multimodal medical image fusion using fuzzy transform”, Journal of Visual Communication and Image Representation, Volume 40, Part A, Pp 197-217, 2016.
  10. Yu Liu, Xun Chen, Zengfu Wang, Z. Jane Wang, Xuesong Wang, “Deep learning for pixel-level image fusion: Recent advances and future prospects”, Information Fusion, Volume 42, Pp 158-173, 2018.

Keywords

Image Fusion, Image Enhancements, Transform Domain, Spatial Domain, Frequency Domain.