In real World conditions, e.g., fog and haze, the surrounding environment contains a large number of microparticles. This creates a medium which interferes with propagating light, changing the appearance of objects within it. When a digital image is captured in this type of medium, the image will be hazy due to blurring and loss of detail. This is a problem for many automated computer vision methods which utilize visual cues in the image. Multiple methods have been proposed to perform image dehazing, but it is difficult to standardize the perceived quality of the estimated clear image. A highly accurate estimation is not always possible because the nature of the problem is m-posed and an exact clear ground truth is usually unavailable. In fact, the goal of many dehazing methods is to simply obtain a visually pleasing understandable image. In this paper, the Pix2pix image to image translation network and the Contrast Limited Adaptive Histogram Equalization (CLAHE) image enhancement method are used to dehaze hazy images. The resulting clear images will be subject to both subjective and objective image quality assessments. Lastly, this paper will also provide an analysis to discuss the important factors in the attempt to obtain a better dehazed image.