Image Fusion: A Review
Keywords:Image Fusion, Fusion Methods, Spatial Domain Fusion, Transform Domain Fusion, Image Quality
At the present time, image fusion is considered as one of the types of integrated technology information, it has played a significant role in several domains and production of high-quality images. The goal of image fusion is blending information from several images, also it is fusing and keeping all the significant visual information that exists in the original images. Image fusion is one of the methods of field image processing. Image fusion is the process of merging information from a set of images to consist one image that is more informative and suitable for human and machine perception. It increases and enhances the quality of images for visual interpretation in different applications. This paper offers the outline of image fusion methods, the modern tendencies of image fusion and image fusion applications. Image fusion can be performed in the spatial and frequency domains. In the spatial domain is applied directly on the original images by merging the pixel values of the two or more images for purpose forming a fused image, while in the frequency domain the original images will decompose into multilevel coefficient and synthesized by using inverse transform to compose the fused image. Also, this paper presents a various techniques for image fusion in spatial and frequency domains such as averaging, minimum/maximum, HIS, PCA and transform-based techniques, etc.. Different quality measures have been explained in this paper to perform a comparison of these methods.
Singh, Er.Simar Preet and Er. Palak Sharma, Image Fusion,2014. International Journal of Advanced Research in Computer Science and Software Engineering.3(4), 206.
Yufeng Zheng, 2011. Image fusion and its applications. Published by InTech Janeza Trdine 9, 51000 Rijeka, Croatia.
Mamta Sharma, 2016. A Review: Image Fusion Techniques and Applications. International Journal of Computer Science and Information Technologies, 7(3) , 1082-1085.
Devyani P. Deshmukh and A. V. Malviya, 2015. Image Fusion an Application of Digital Image Processing using Wavelet Transform. International Journal of Scientific & Engineering Research, 6(11) ,1247-1250.
Russell Haidar Jassim,2017. Image Denoising Using Fusion Technique Based on DWT Coefficient. Msc. Thesis. College of Information Technology, University of Babylon.
Priya D. Vora and Ms. Neeta Chudasama,2015. Different Image Fusion Techniques and Parameters: A Review . International Journal of Computer Science and Information Technologies , 1(6) ,889-891.
Krishnamoorthy, Shivsubramani and K P Soman., 2010.Implementation and Comparative Study of Image Fusion Algorithm. International Journal of Computer Applications, 9(2).
Choodarathnakara A. L., Dr. T. Ashok Kumar, Dr. Shivaprakash Koliwad, and Dr. C. G. Patil, 2012.Assessment of Different Fusion Methods Applied to Remote Sensing Imagery.(IJCSIT) International Journal of Computer Science and Information Technologies,3(6), 5447-5453.
Sahu, Deepak Kumar and M.P.Parsai,2012. Different Image Fusion Techniques A Critical Review.International Journal of Modern Engineering Research (IJMER), 5 (2) , 4298-4301.
Jawale, Miss.Yogita and Mrs.A.G.Andurkar, 2013. Implementation of Image Fusion Technique Using Wavelet Transform. International Journal of Science Engineering and Technology Research (IJSETR), 2(3).
Zhu, Huiping, Bin Wu and Peng Ren, 2013. Medical Image Fusion Based on Wavelet Multi-Scale Decomposition. Journal of Signal and Information Processing,4, 218-221.
C. Pavithra and S. Bhargavi, 2013. The fusion of Two Images Based on Wavelet Transform. International Journal of Innovative Research in Science Engineering and Technology, 2(5).
Mandhare, Rohan Ashok, Pragati Upadhyay and Sudha Gupta, 2013. Pixel Level Image Fusion Using Brovey Transform and Wavelet Transform .International Journal of Advanced Research in Electrical Electronics and Instrumentation Engineering, 2(6).
Rani, Kusum and Reecha Sharma, 2013. Study of Image Fusion Using Discrete wavelet and Multiwavelet Transform. International Journal of Innovative Research in Computer and Communication Engineering,1(4).
Mishra, Hari Om Shanker and Smriti Bhatnagar, 2014. MRI and CT Image Fusion Based on Wavelet Transform.International Journal of Information and Computation Technology,4(1), 47-52.
Tawade, Laxman, Abida Bapu Aboobacker and Firdos Ghante, 2014. Image Fusion Based on Wavelet Transforms. International Journal of Bio-Science and Bio-Technology,6(3),149-162.
Agarkar, Prerana GP and rof. Deepali R Sale, 2015. Efficient MRI and CT Images Fusion Technique: Analysis. International Journal of Advanced Research in Computer Science and Software Engineering,5(7).
Israa Hadi Ali and Russell H. Al_taie, 2016. Wavelet coefficient fusion method -based image denoising. Research Journal of Applied Sciences,10 (11), 1045-1049.
Morris and R.S. Rajesh, 2014. two-stage spatial domain image fusion techniques. intact journal on image and video processing: special issue on video processing for multimedia systems,1 (5), 895-896.
Mamta M. Mistry, Brijesh Vala, 2016. Survey on Different Image Fusion Techniques. International Research Journal of Engineering and Technology (IRJET),3(3),933-934.
Bhuvaneswari Balachander and D. Dhanasekaran,2016. comparative study of image fusion techniques in spatial and transform domain. ARPN Journal of Engineering and Applied Sciences, 9 (11), 5779-5783.
Firouz Abdullah Al-Wassai1, N.V. Kalyankar, Ali A. Al-Zuky,2011. The IHS Transformations Based Image Fusion. Journal of Advanced Research in Computer Science, 5 (2).
Johnson Sudhakar, J.Monica Esther M.E, D.Annapoorani and F.Richard Singh Samuel,2014. Study of Image Fusion- Techniques, Method and Applications. International Journal of Computer Science and Mobile Computing, 3(11),470-471.
Navneet Kaur, Madhu Bahl, Harsimran Kaur, 2014. review on: Image Fusion Using Wavelet and Curvelet Transform. (IJCSIT) International Journal of Computer Science and Information Technologies, 5 (2), 2467-2470.
R.Maruthi and I.Lakshmi, 2017. Multi-Focus Image Fusion Methods – A Survey. Journal of Computer Engineering,19(4), 9-15.
Shriniwas T. Budhewar, 2014. Wavelet and Curvelet Transform based Image Fusion Algorithm. International Journal of Computer Science and Information Technologies, 3 (5), 3703-3705.
Starck, J. L., Candes, E. J., and Donoho, D.L., 2003. Gray and Color Image Contrast Enhancement by the Curvelet Transform. IEEE Trans. Image Processing., 12(6), 706-717.
Barkha Panda, 2016. Image Fusion Using a Combination of Wavelet and Curvelet Fusion. International Journal of Advanced Research in Computer Engineering & Technology (IJARCET), 8 (5).
Abbas and Heba Khudhair,2013. A Study of Digital Image Fusion Techniques based on Contrast and Correlation Measures. PhD. Thesis, College of Science, Al-Mustansiriyah University, 28-29.
R.Johnson Sudhakar, J.Monica Esther M.E, D.Annapoorani and F.Richard Singh Samuel, 2014.Study of Image Fusion- Techniques, Method and Applications. International Journal of Computer Science and Mobile Computing,3(11), 469-474. (wavelet, application)
Ms. Mukta V. Parvatikar and Prof. Gargi S. Phadke, 2014. Comparative Study of Different Image Fusion Techniques. International Journal of Scientific Engineering and Technology, 3(4), 375-378. (Methods application)
Saleha Masood, Muhammad Sharif, Mussarat Yasmin, Muhammad Alyas Shahid, and Amjad Rehman, 2017. Image Fusion Methods: A Survey. Journal of Engineering Science and Technology Review, 10(6), 189-190.
Dewangan, Namrata and Agam Das Goswami, 2012. Image Denoising Using Wavelet Thresholding Methods. International Journal of Engineering science & management, 2 (2), 271 -275.
Dhirendra Mishra and Bhakti Palkar,2015. Image Fusion Techniques: A Review. International Journal of Computer Applications, 9 (130), 7-10.
Vaishalee G. Patel, Asso. Prof. S.D.Panchal,2014. A Review on Image Fusion Techniques. International Journal of Advanced Engineering and Research Development (IJAERD), 3 (11), 1- 4.