Abstract
This paper presents an effective fusion technique for an exposure bracketed pair of images, which may contain motion blur from moving objects or hand trembling. Exposure fusion is a technique to represent a high dynamic scene by fusing differently exposed images. Existing exposure fusion methods either assume the input images are perfectly aligned or conduct an additional alignment step before/during the fusion process. To have a high quality result without resorting to image alignment, we propose to fuse a histogram-transformed image with the short-exposed image to preserve desired properties from the input image pair. We model the fuse problem as determining the fusing map via Markov Random Field in terms of spatial continuity and two fusion criteria. Our experiments demonstrate that our results are comparable with existing methods which include additional alignment steps.