Image Fusion using Cross Bilateral Filter and Wavelet Transform Domain
Kapil Joshi1, N.K.Joshi2, Manoj Diwakar3
1Kapil Joshi, Department of Computer Science & Engineering, Uttaranchal University, Dehradun (Uttarakhand), India.
2N.K. Joshi, Department of Computer Science & Engineering, Uttaranchal University, Dehradun (Uttarakhand), India.
3Manoj Diwakar, Department of Computer Science & Engineering, DIT University, Dehradun (Uttarakhand), India.
Manuscript received on 25 March 2019 | Revised Manuscript received on 06 April 2019 | Manuscript Published on 11 April 2019 | PP: 110-115 | Volume-8 Issue-4C, April 2019 | Retrieval Number: D24300484C19/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The actual goal of fused images is all about to reduce the complexity of visual data of any images using the process of merging two relevant image of the similar scene. In this paper, an algorithm on fusion concept through discrete wavelet transforms (DWT) and cross bilateral filter (CBF) is introduced. In this proposed detailed work, all existing images are dissolved into obscure frequency sub bands and advanced frequency sub bands with the help of discrete wavelet transform (DWT).After converting these images will be categorized into obscure frequency sub bands transformed images and advanced frequency sub bands transformed images. We have used pixel average method and weighted average method but pixel averaging method is for low frequency sub bands transformed images meanwhile weighted averaging method is applicable for high frequency sub bands transformed images. Further the weights are calculated by cross bilateral filter (CBF) on both types of images. At the end of process, DWT is applied to rebuild the fused resultant images over the fused some coefficients. The introduced work completely tested on various multi-focus images and other multi-sensors images. Existing methods results and proposed methods results are simultaneously compared with the various metrics just for qualitative measurement. For future prospective, the proposed results will be better than previous existing completed work in the form of qualitative as well as the quantitative parameters.
Keywords: Image Fusion, Discrete Wavelet Transform, Inverse Discrete Wavelet Transform, Cross Bilateral Filter.
Scope of the Article: Image Security