Image Processing Strategies for Fusion of Multiple Images : A Comprehensive Analysis

Authors(2) :-Prabhjit Kaur, Prabhpreet Kaur

The digital image processing is capable of handling the problems extracted out of several domains. Information collected over the several domains is required to be filtered. The process of extracting information out of several domains is known as image fusion. Application areas of image fusion could be many. This paper highlights the application of image fusion in fields of health care using MRI and CT images etc. The phases associated with image fusion include feature detection, feature matching, transform model estimation and image resampling and transformation. Each of these phases is elaborated for detecting the enhancement parameter for future endeavours. Comparative analysis is presented to determine the optimal technique that can be worked upon to obtain optimal parameter listening.

Authors and Affiliations

Prabhjit Kaur
MTECH Guru Nanak Dev University, Amritsar, Punjab, India
Prabhpreet Kaur
MTECH Guru Nanak Dev University, Amritsar, Punjab, India

Image processing, image fusion, feature detection, matching, transform model estimation, image resampling and transformation

  1. N.Singla, "A Comparative Study of Noising And Denoising Technique In Image Processing," vol.4, no.3, pp.38-42, 2016.
  2. Y.Ma, D.Lin, B.Zhang, Q.Liu, and J.Gu, "A Novel Algorithm of Image Gaussian Noise Filtering based on PCNN Time Matrix," in 2007 IEEE International Conference on Signal Processing and Communications, 2007, pp.1499-1502.
  3. P.Yuvarani, "Image Denoising and Enhancement for Lung Cancer Detection using Soft Computing Technique," pp.27-30, 2012.
  4. S.Huda, J.Yearwood, H.F.Jelinek, M.M.Hassan, and M.Buckland, "A hybrid feature selection with ensemble classification for imbalanced healthcare data?: A case study for brain tumor diagnosis," vol.3536, no.c, pp.1-13, 2016.
  5. I.Reducindo, E.R.Arce-santana, D.U.Campos-delgado, F.Vigueras-g, A.R.Mej, and G.Rizzo, "Non-rigid Multimodal Medical Image Registration Based on the Conditional Statistics of the Joint Intensity Distribution," vol.7, pp.126-133, 2013.
  6. V.Bhavana and H.K.Krishnappa, "Multi-Modality Medical Image Fusion using Discrete Wavelet Transform," vol.70, pp.625-631, 2015.
  7. I.Kosesoy, M.Cetin, and A.Tepecik, "A Toolbox for Teaching Image Fusion in Matlab," Procedia - Soc.Behav.Sci., vol.197, no.February, pp.525-530, 2015.
  8. P.B.Dasgupta, "Analytical Comparison of Noise Reduction Filters for Image Restoration Using SNR Estimation," vol.17, no.3, pp.121-124, 2014.
  9. R.Kaushik, R.Kumar, and J.Mathew, "On Image Forgery Detection Using Two Dimensional Discrete Cosine Transform and Statistical Moments," vol.70, pp.130-136, 2015.
  10. I.D.T, B.Goossens, and W.Philips, "MRI Segmentation of the Human Brain?: Challenges , Methods , and Applications," vol.2015, 2015.
  11. D.Van De Ville, M.Nachtegael, D.Van Der Weken, E.E.Kerre, W.Philips, I.Lemahieu, and S.Member, "Noise Reduction by Fuzzy Image Filtering," vol.11, no.4, pp.429-436, 2003.
  12. P.Dave and M.Tech, "Study and Analysis of Face Recognition system using Principal Component Analysis ( PCA )."
  13. X.Luan, B.Fang, L.Liu, W.Yang, and J.Qian, "Extracting sparse error of robust PCA for face recognition in the presence of varying illumination and occlusion," Pattern Recognit., vol.47, no.2, pp.495-508, 2014.
  14. K.H.An, S.H.Park, Y.S.Chung, K.Y.Moon, and M.J.Chung, "Features for Face Detection Based on Ada-LDA," pp.1117-1122, 2009.
  15. S.Avinash, "An Improved Image Processing Analysis for the Detection of Lung Cancer using Gabor Filters and Watershed Segmentation Technique."
  16. M.Satone and G.Kharate, "Feature Selection Using Genetic Algorithm for Face Recognition Based on PCA , Wavelet and SVM," vol.6, no.1, pp.39-52, 2014.
  17. M.Imran and A.Ghafoor, "A PCA-DWT-SVD based Color Image Watermarking," pp.1147-1152, 2012.
  18. V.Ponomaryov, "Computer-aided detection system based on PCA/SVM for diagnosis of breast cancer lesions," 2015 Chil.Conf.Electr.Electron.Eng.Inf.Commun.Technol., pp.429-436, 2015.
  19. P.N.Dangat and P.S.D.Joshi, "Efficient Disease Detection Approach Based on MRI and CT Images Fusion Technique," vol.3, no.7, pp.918-922, 2014.
  20. M.Rahate and R.Atyali, "Image Fusion to Enhance the Disease Diagnosis," pp.61-64.

Publication Details

Published in : Volume 3 | Issue 2 | January-February 2018
Date of Publication : 2018-02-28
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 245-252
Manuscript Number : CSEIT1831358
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Prabhjit Kaur, Prabhpreet Kaur, "Image Processing Strategies for Fusion of Multiple Images : A Comprehensive Analysis", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 2, pp.245-252, January-February-2018.
Journal URL :

Article Preview

Follow Us

Contact Us