The aim of image fusion is to combine relevant information from two or more source images into one single image such that the single image contains better information than all the source images. Fusion algorithms are categorized as the basic function algorithm and pyramid (Laplacian and Gaussian pyramid) based algorithm. Now a day’s pyramid based algorithm is used mostly, the need of image fusion is to improve the quality of image for an object taken by different sensors. The fused image contains high spectral information as compared to simple one. The fusion process for different images acquired from different sensors is important for many applications such as medical imaging, microscopic imaging, remote sensing, computer vision and robotics etc. In this paper, we apply this technique to enhance the contrast of the image that improves the quality of visible image without introducing unrealistic visual appearances and is useful for improving quality of image with the modification of brightness differences in the dark (grayish) or bright regions at the expense of the brightness differences in the other regions. The proposed method improves the optimization problem that maximizes average local contrast and global contrast of an image. The quality of image is justified with the help of calculated entropy levels.

Full text: IJEIR_814_Final.pdf