  In this paper, a novel inverse tone mapping method using a convolutional
neural network (CNN) with LDR based learning is proposed. In conventional
inverse tone mapping with CNNs, generated HDR images cannot have absolute
luminance, although relative luminance can. Moreover, loss functions suitable
for learning HDR images are problematic, so it is difficult to train CNNs by
directly using HDR images. In contrast, the proposed method enables us not only
to estimate absolute luminance, but also to train a CNN by using LDR images.
The CNN used in the proposed method learns a transformation from various input
LDR images to LDR images mapped by Reinhard's global operator. Experimental
results show that HDR images generated by the proposed method have
higher-quality than HDR ones generated by conventional inverse tone mapping
methods,in terms of HDR-VDP-2.2 and PU encoding + MS-SSIM.
