  High dynamic range (HDR) imaging enables to immortalize natural scenes
similar to the way that they are perceived by human observers. With regular low
dynamic range (LDR) capture/display devices, significant details may not be
preserved in images due to the huge dynamic range of natural scenes. To
minimize the information loss and produce high quality HDR-like images for LDR
screens, this study proposes an efficient multi-exposure fusion (MEF) approach
with a simple yet effective weight extraction method relying on principal
component analysis, adaptive well-exposedness and saliency maps. These weight
maps are later refined through a guided filter and the fusion is carried out by
employing a pyramidal decomposition. Experimental comparisons with existing
techniques demonstrate that the proposed method produces very strong
statistical and visual results.
