Image Fusion Technique Based on Hybrid Whale Optimization Algorithm Simulated Annealing (hWOA-SA)
Vandana Nawaria1, Shailaja Yogesh Kanawade2, Vikas Soni3
1Vandana Nawaria, Dept. of ECE, Modi Institute of Technology, Kota, Rajasthan, India.
2Shailaja Yogesh Kanawade, Dept. of ECE, Modi Institute of Technology, Kota, Rajasthan, India.
3Vikas Soni, Dept. of ECE, Modi Institute of Technology, Kota, Rajasthan, India.
Manuscript received on 01 September 2019. | Revised Manuscript received on 22 September 2019. | Manuscript published on 30 September 2019. | PP: 19-24 | Volume-8 Issue-11, September 2019. | Retrieval Number: J98960881019/2019©BEIESP | DOI: 10.35940/ijitee.J9896.0981119
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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: Curvelet transform is a multiscale directional transformer, which allows optimal non-adaptive sparse representation of object with edge. In this paper, a new image fusion technique has been developed by combination of whale optimization algorithm (WOA) and simulated annealing (SA) along with curvelet transform. The resulting combined algorithm is abbreviated as hybrid whale optimization algorithm with simulated annealing. Initially, hWOA-SA has been applied to enhancing the quality of image using de-noising scheme. Afterwards, the curvelet transform has been employed to carry out the fusion of images. In terms of PSNR, the curvelet transform exhibits the better performance. The effectiveness and validation of the proposed scheme has been carried-out using quality matrices. The performance analysis is carried out after checking the effectiveness of proposed approach by evaluating the various parameters such as: RSME, PFE, MAE, CORR, SNR, PSNR, MI, UQI and SSIM and compared with numerous techniques. Simulation results obtained from proposed hWOA-SA based image fusion are very competitive and better than other image fusion technique available in the literature.
Keywords: Curvelet transform, Hybrid whale optimization algorithm simulated annealing (hWOA-SA). PSNR, RMSE, Saras type image.
Scope of the Article: