Modern digital cameras have very limited dynamic range, which makes them unable to capture the full range of illumination in natural scenes. Since this prevents them from accurately photographing visible detail, researchers have spent the last two decades developing algorithms for high-dynamic range (HDR) imaging which can capture a wider range of illumination and therefore allow us to reconstruct richer images of natural scenes. The most practical of these methods are stack-based approaches which take a set of images at different exposure levels and then merge them together to form the final HDR result. However, these algorithms produce ghost-like artifacts when the scene has motion or the camera is not perfectly static. In this paper, we present an overview of state-of-the-art deghosting algorithms for stack-based HDR imaging and discuss some of the tradeoffs of each.