Fully-Automatic Inverse Tone Mapping Algorithm Based On Dynamic Mid-Level Mapping
High Dynamic Range (HDR) displays can show images with higher color contrast levels and peak luminosities than the common Low Dynamic Range (LDR) displays. However, most existing video content is recorded and/or graded in LDR format. To show LDR content on HDR displays, it needs to be up-scaled using a so-called inverse tone mapping algorithm. Several techniques for inverse tone mapping have been proposed in the last years, going from simple approaches based on global and local operators to more advanced algorithms such as neural networks. Some of the drawbacks of existing techniques for inverse tone mapping are the need for human intervention, the high computation time for more advanced algorithms, limited low peak brightness, and the lack of the preservation of the artistic intentions. In this paper, we propose a fully-automatic inverse tone mapping operator based on mid-level mapping capable of real-time video processing. Our proposed algorithm allows expanding LDR images into HDR images with peak brightness over 1000 nits, preserving the artistic intentions inherent to the HDR domain. We assessed our results using the full-reference objective quality metrics HDR-VDP-2.2 and DRIM, and carrying out a subjective pair-wise comparison experiment. We compared our results with those obtained with the most recent methods found in the literature. Experimental results demonstrate that our proposed method outperforms the current state of the art of simple inverse tone mapping methods and its performance is similar to other more complex and time-consuming advanced techniques.
An Experimental Study on the Perceived Quality of Natively Graded versus Inverse Tone Mapped High Dynamic Range Video Content on Television
High Dynamic Range (HDR) television promises to display higher brightness and deeper black levels and thus more vivid and realistic images. However, home video distribution, video broadcasting and legacy content have been created to be displayed on standard dynamic range screens (SDR). In order to display this content on an HDR screen, it needs to be inversely tone mapped. A psychophysical experiment has been performed to test how viewers evaluate the difference between natively graded and different tone mapped HDR television content. Results indicate that viewers prefer natively graded HDR content, followed by inverse tone mapping algorithms starting from videos with compressed dynamic range. Users disliked videos that were linearly stretched from standard SDR. In addition, a significant effect of type of sequence was found, with a preference for light scenes with low contrast. The results of this experimental study provide insight into the understanding of perceptual HDR image rendering and will aid in designing strategies for inverse tone mapping.
Fully-automatic inverse tone mapping preserving the content creator's artistic intentions
High Dynamic Ranges (HDR) displays can show images with higher color contrast levels and peak luminosities than the common Low Dynamic Range (LDR) displays. However, most existing video content is recorded and/or graded in LDR format. To show this LDR content on HDR displays, a dynamic range expansion by using an Inverse Tone Mapped Operator (iTMO) is required. In addition to requiring human intervention for tuning, most of the iTMOs don't consider artistic intentions inherent to the HDR domain. Furthermore, the quality of their results decays with peak brightness above 1000 nits. In this paper, we propose a fully-automatic inverse tone mapping operator based on mid-level mapping. This allows to expand LDR images into HDR with peak brightness over 1000 nits, preserving the artistic intentions inherent to the HDR domain. We assessed our results using full-reference objective quality metrics as HDR-VDP-2.2 and DRIM. Experimental results demonstrate that our proposed method outperforms the current state of the art.
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