Image Fusion Methods and Comparisons Based on Various Metrics

With the increase in the development of sensing technology and sensing devices, more and more data are getting available to the user hence increasing the human workload to greater extent. It becomes difficult for human operator to simultaneously operate, analyze and interpret information from multiple images. It leads to the need of image fusion techniques. In this research paper, we have considered multi-focal images as source input images and three methods of fusion, Weighted Average, PCA, and the hybrid proposed method. The methods are evaluated using various evaluation metrics. Study shows us that proposed fusion method gives better result compare to other methods studied. A good fusion is the one which produces output fusion result with maximum spectral detail. Spatial resolution is equally important in the output fused result than available with any single source image.