Journal of Soft Computing Paradigm
IRO Journals
Volume 2 — Issue 4 — December 2020

Highly Precise Modified Blue Whale Method Framed by Blending Bat and Local Search Algorithm for the Optimality of Image Fusion Algorithm

https://doi.org/10.36548/jscp.2020.4.001
Sayantan Dutta
Department of Electronics and Telecommunication Engineering Indian Institute of Engineering Science and Technology, Shibpur Howrah-711103
Ayan Banerjee
Department of Electronics and Telecommunication Engineering Indian Institute of Engineering Science and Technology, Shibpur Howrah-711103
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How to Cite

Dutta, Sayantan, and Ayan Banerjee. 2020. “Highly Precise Modified Blue Whale Method Framed by Blending Bat and Local Search Algorithm for the Optimality of Image Fusion Algorithm”. Journal of Soft Computing Paradigm 2 (4): 195-208. https://doi.org/10.36548/jscp.2020.4.001.
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Keywords

— WOA
— modified WOA
— prey
— MWOA
— BA
— LSS
— metaheuristic optimization
— heuristic optimization
Published: 07-09-2020

Abstract

Image fusion has gained huge popularity in the field of medical and satellite imaging for image analysis. The lack of usages of image fusion is due to a deficiency of suitable optimization techniques and dedicated hardware. In recent days WOA (whale optimization algorithm) is gaining popularity. Like another straightforward nature-inspired algorithm, WOA has some problems in its searching process. In this paper, we have tried to improve the WOA algorithm by modifying the WOA algorithm. This MWOA (modified whale optimization algorithm) algorithm is amalgamed with LSA (local search algorithm) and BA (bat algorithm). The LSA algorithm helps the system to be faster, and BA algorithm helps to increase the accuracy of the system. This optimization algorithm is checked using MATLAB R2018b. Simulated using ModelSim, and the synthesizing is done using Xilinx Vivado 18.2 synthesis tool. The outcome of the simulation result and the synthesis result outshine other metaheuristic optimization algorithms.

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