  In this paper, a novel image enhancement network is proposed, where HDR
images are used for generating training data for our network. Most of
conventional image enhancement methods, including Retinex based methods, do not
take into account restoring lost pixel values caused by clipping and
quantizing. In addition, recently proposed CNN based methods still have a
limited scope of application or a limited performance, due to network
architectures. In contrast, the proposed method have a higher performance and a
simpler network architecture than existing CNN based methods. Moreover, the
proposed method enables us to restore lost pixel values. Experimental results
show that the proposed method can provides higher-quality images than
conventional image enhancement methods including a CNN based method, in terms
of TMQI and NIQE.
