Pattern recognition, Image enhancement, Feature extraction are the key research areas in image processing. It can be applied to many applications such as satellite, medical, military, infrared imaging and LIDAR. There are many existing algo in im pr, several image enhancement techniques have been developed, such as histogram equalization, contrast stretching, bit plane slicing, averaging, etc. but the ambiguity is because of missing evaluation metrics, which leads to uncertainity in deciding the algorithm that can perform better. There are some uncertainties regarding these above techniques such as edge detection, oversmoothing, blurring and deformation of edges. In this paper, we considered edge detection as one of the uncertainty and the evaluation metrics such as SSIM (Structural Similarity Index) and VIF(Visual Information Fidelity) has been applied to the images to measure the image quality. The SSIM and VIF have been applied to the different types of images such as Grayscale, Color, Infrared, LIDAR, Microscopic and Biomedical Images. In the present work evaluation metrics are applied to the original image and egde detected image, thus from experimental results it is observed that the proposed algorithm works well for measuring the quality of spatial resolution enhanced hyper spectral images.