Optimal Image Fusion Algorithm using Modified Whale Optimization Algorithm Amalgamed with Local Search and BAT Algorithm

Abstract

Image fusion has an extensive application in the area of medical and satellite image analysis. Having such large applicability, the uses of image fusion is restricted because of the lack of precise algorithm and dedicated hardware. Researchers have tried to use the metaheuristic algorithm in the image processing field. The WOA (whale optimization algorithm) is one of the most popular metaheuristic algorithms used in recent days, but any such straight forward metaheuristic algorithm has some drawbacks. To overcome this drawback, a MWOA (modified WOA) has been proposed in this paper. This modified WOA is incorporated with LSA and BA algorithm. LSA makes this WOA more accurate, and BA makes this system faster. The problem of premature convergence and trapping of local minima is also shorted by using this MWOA. This Modified WOA have greater accuracy for identifying the object which has been compared with other heuristic and metaheuristic algorithm. The optimization algorithm is tasted by using MATLAB R2018b. The proposed design is synthesized using Xilinx Vivado 18.2 synthesis tool and simulated using ModelSim. The outcomes of the synthesis report and simulation of the circuit outshine other metaheuristic optimization approach. This MWOA is performed by using our own designed algorithm.