  There are shadow and highlight regions in a low dynamic range (LDR) image
which is captured from a high dynamic range (HDR) scene. It is an ill-posed
problem to restore the saturated regions of the LDR image. In this paper, the
saturated regions of the LDR image are restored by fusing model-based and
data-driven approaches. With such a neural augmentation, two synthetic LDR
images are first generated from the underlying LDR image via the model-based
approach. One is brighter than the input image to restore the shadow regions
and the other is darker than the input image to restore the high-light regions.
Both synthetic images are then refined via a novel exposedness aware saturation
restoration network (EASRN). Finally, the two synthetic images and the input
image are combined together via an HDR synthesis algorithm or a multi-scale
exposure fusion algorithm. The proposed algorithm can be embedded in any smart
phones or digital cameras to produce an information-enriched LDR image.
