Fusion of Wireless Sensor Images Using Improved Harmony Search Algorithm with Perturbation Strategy and Elite Opposition Based Learning

The idea of image fusion in Wireless Sensor Network (WSN) is to combine the important features of the various images from the multi-focus cameras. Generally, image fusion in WSN consumes more energy and bandwidth to process the images. Hence to reduce the above constraints, it is necessary to reduce the computation time of the image fusion algorithm. In this paper, a histogram-based multi-thresholding with optimization is proposed to fuse the images. Further, an attempt has been made in this paper, by considering the Improved Harmony Search algorithm with Perturbation Strategy (IHSPS) as an optimization technique. In addition to this, the elite opposition based learning is also incorporated with the IHSPS to improve the local search ability. From the simulation results, it is understood that the incorporation of IHSPS with multi-thresholding outperforms the existing multi-thresholding based image fusion algorithms in terms of computation time and image quality.