Abstract
Image fusion focuses on combining information from different images of a scene to obtain more useful information for various applications. A large number of transform techniques have been used for image fusion process that include DCT, DST, DWT, Kekre’s wavelet transform and Walsh transform. This paper compares the quality of image fusion obtained using these transforms. These techniques have been compared with each other in the past using different quality indices that include mean, variance, standard deviation, RMSE, PSNR and SF. This paper attempts to compare these fusion techniques using the various quality indices so as to get a clear picture about relative performance of these techniques. The experimental results on some standard test images demonstrate that DWT and DCT are better compared to other.
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References
Arpita Das, Mahua Bhattacharya, “Evolutionary algorithm based automated medical image fusion technique comparative study with fuzzy fusion approach”, Nature & Biologically Inspired Computing, pp: 269–274, 9–11 Dec 2009.
Tao Wu, Xiao-Jun Wu, Xiao-Qing Luo, “A study on fusion of different resolution images”, Procedia Engineering, Vol. 29, pp: 3980–3985, 2012.
Peijun Du, Sicong Liu, Paolo Gamba, Kun Tan and Junshi Xia, “Fusion of difference images for change detection over urban areas”, IEEE journal of selected topics in applied earth observations and remote sensing, Vol. 5, No. 4, Aug 2012.
Peijun Du, Sicong Liu, Junshi Xia, Yindi Zhao, “Information fusion techniques for change detection from multi temporal remote sensing images”, Information Fusion 14, pp: 19–27, 2013.
Ren C. Luo, Chun Chi Lai, “Multisensor fusion based concurrent environment mapping and moving object detection for intelligent service robotics”, IEEE transactions on industrial electronics, Vol. 61, No. 8, pp: 4043–4051, Aug 2014.
Y. Asnath Victy Phamila, R. Amutha, “Discrete cosine transform based fusion of multi focus images for visual sensor networks”, Signal Processing 95, pp: 161–170, 2014.
Mohammd Bagher Akbari haghighat, Ali Aghagolzadeh, Hadi Seyedarabi, “Real time fusion of multi focus images for visual sensor networks”, 6th Iranian conference of machine vision and image processing, pp: 1–6, 27–28, Oct 2010.
Liu Cao, Longxu Jin, Hongjiang Tao, Guoning Li, Zhuang Zhuang,Yanfu Zhang, “Multifocus image fusion based on spatial frequency in discrete cosine transform domain”, IEEE signal processing letters, Vol. 22, No. 2, pp: 220–224, Feb 2015.
B. Roopa, Sunilkumar S. Manvi, “Image fusion techniques for wireless sensor networks: Survey”, ITSI Transactions on Electrical and Electronics Engineering, 2320–8945, Vol. 2, pp: 13–19, 2014.
Shivdeep Kaur, Rajiv Mahajan, “Evaluating the short comings of digital image fusion techniques”, International Journal on recent and innovation trends in computing and communication, Vol. 2, No. 5, pp: 1162–1167, May 2014.
Qian Zhang, Zhiguo Cao, Zhongwen Hu, Yonghong Jia, Xiaoliang Wu, “Joint image registration and fusion for panchromatic and multispectral images”, IEEE geoscience and remote sensing letters, Vol. 12, No. 3, pp: 467–471, Mar 2015.
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Kulkarni, J.S., Bichkar, R.S. (2018). Comparative Analysis of Image Fusion Using DCT, DST, DWT, Walsh Transform and Kekre’s Wavelet Transform. In: Dash, S., Das, S., Panigrahi, B. (eds) International Conference on Intelligent Computing and Applications. Advances in Intelligent Systems and Computing, vol 632. Springer, Singapore. https://doi.org/10.1007/978-981-10-5520-1_22
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DOI: https://doi.org/10.1007/978-981-10-5520-1_22
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