Call for Paper - January 2023 Edition
IJCA solicits original research papers for the January 2023 Edition. Last date of manuscript submission is December 20, 2022. Read More

Image Fusion on Coloured and Gray Scale Multi Focus Images by using Hybrid DWT-DCT

Print
PDF
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
Mamta Sharma, Sarika Khandelwal
10.5120/ijca2016911861

Mamta Sharma and Sarika Khandelwal. Image Fusion on Coloured and Gray Scale Multi Focus Images by using Hybrid DWT-DCT. International Journal of Computer Applications 152(9):30-34, October 2016. BibTeX

@article{10.5120/ijca2016911861,
	author = {Mamta Sharma and Sarika Khandelwal},
	title = {Image Fusion on Coloured and Gray Scale Multi Focus Images by using Hybrid DWT-DCT},
	journal = {International Journal of Computer Applications},
	issue_date = {October 2016},
	volume = {152},
	number = {9},
	month = {Oct},
	year = {2016},
	issn = {0975-8887},
	pages = {30-34},
	numpages = {5},
	url = {http://www.ijcaonline.org/archives/volume152/number9/26350-2016911861},
	doi = {10.5120/ijca2016911861},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Any piece of information is meaningful only when it is able to convey the content about it. The clarity and quality of information is important. Image Fusion is a technique to improve the quality and quantity of information from a set of images. By the process of image fusion the more information from each of the given images is combining together to generate a resultant image whose quality is maximum to any of the input images.

We proposed a Hybrid DWT-DCT method to fuse multi focus images. In this technique we convert the image data from spatial domain to transform domain.. Then decompose the transform data into four parts that is LL, LH, HL, HH part. This decomposition Process again applies in LL part at two levels. After this three level decomposition we combine the input image data by applying average method using DCT and get fused data. This data are in transform domain again convert to spatial domain by applying IDCT and IDWT method and get final fused image with better visual Quality. After getting the result of fused image we compare the quality measure parameters of different technique like PCA, DCT, average pixel, maximum pixel, minimum pixel, HDWT method to hybrid DWT-DCT method. And conclude that the PSNR value and Entropy of fused image have better result as compare to other techniques. Due to this the fused image has better visual Quality as well as more informative data would contain in fused image.

References

  1. James, Alex Pappachen, and Belur V. Dasarathy. "Medical image fusion: A survey of the state of the art." Information Fusion 19 (2014): 4-19.
  2. Abuturab, Muhammad Rafiq. "Multiple color-image fusion and watermarking based on optical interference and wavelet transform." Optics and Lasers in Engineering (2016).
  3. Galande, Ashwini, and Ratna Patil. "The art of medical image fusion: A survey." Advances in Computing, Communications and Informatics (ICACCI), 2013 International Conference on. IEEE, 2013.
  4. Li, Shutao, Bin Yang, and Jianwen Hu. "Performance comparison of different multi-resolution transforms for image fusion." Information Fusion 12, no. 2 (2011): 74-84
  5. Kusum Rani, Reecha Sharma , “Study of different image fusion algorithm” International Journal Of Emerging Technology And Advanced Engineering ( IJETAE) volume 3 , issue 5 , may 2013
  6. K. Kannan , S. Arumuga Perumal , “ Fusion of multifocused images using HDWT for machine vision ” International Journal Of Computer Science And Engineering. Volume 2 , no 5, ( 2011 ) ISSN 0976 – 5166
  7. Srinivasa Rao Dammavalam, Seetha Maddala and Krishna Prasad MHM, “Quality assessment of pixel-level image Fusion using fuzzy logic” International Journal on Soft Computing ( IJSC ) Vol.3, No.1, February 2012
  8. S. S. Bedi, Rati Khandelwal “Comprehensive and Comparative Study of Image Fusion Techniques” International Journal of Soft Computing and Engineering (IJSCE) ISSN: 2231-2307, Volume-3, Issue-1, March 2013
  9. Mr. Vipin Wani, Prof. Mukesh Baghe, Prof. Hitesh Gupta, “A Comparative Study of Image Fusion Technique Based on Feature Using Transforms Function” International Journal of Emerging Technology and Advanced Engineering. ISSN 2250-2459, ISO 9001:2008, Volume 3, Issue 11, November 2013
  10. Ms. Rubeena Vohra Dr. K.C. Tiwari, “A Review and Assessment of Fusion Algorithms on Gray Scale Images” International Journal of Electronics, Electrical and Computational System IJEECS ISSN 2348-117X Volume 4, Special Issue September 2015
  11. PreetKaur, Geetulalit, “Comparative Analysis of DCT, DWT & LWT for Image Compression” International Journal of Innovative Technology and Exploring Engineering (IJITEE) Volume-1, Issue-3, August 2012
  12. Shalima , Dr. Rajinder Virk, “Review Of Image Fusion Techniques” International Research Journal of Engineering and Technology (IRJET) ISSN: 2395 -0056 , Volume: 02 Issue: 03 | June-2015
  13. Harmandeep Kaur, Er. Jyoti Rani, “Analytical Comparison of Various Image Fusion Techniques”International Journal of Advanced Research in Computer Science and Software Engineering , ISSN: 2277 128X, Volume 5, Issue 5, May 2015
  14. Dr.S.S.Bedi, Mrs.Jyoti Agarwal, Pankaj Agarwal, “Image Fusion Techniques and Quality Assessment Parameters for Clinical Diagnosis: A Review” , International Journal of Advanced Research in Computer and Communication Engineering , ISSN (Online) : 2278-1021, Vol. 2, Issue 2, February 2013

Keywords

Multi focus image, Fused Image, PSNR, Entropy, DWT, DCT, PCA, HDWT, Hybrid DWT-DCT