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Chen Xiangyu ; Zhang Zhengwen ; Ren Jimmy S. ; Tian Lynhoo ; Qiao Yu ; Dong Chao

Abstract
Nowadays modern displays are capable to render video content with highdynamic range (HDR) and wide color gamut (WCG). However, most availableresources are still in standard dynamic range (SDR). Therefore, there is anurgent demand to transform existing SDR-TV contents into their HDR-TV versions.In this paper, we conduct an analysis of SDRTV-to-HDRTV task by modeling theformation of SDRTV/HDRTV content. Base on the analysis, we propose a three-stepsolution pipeline including adaptive global color mapping, local enhancementand highlight generation. Moreover, the above analysis inspires us to present alightweight network that utilizes global statistics as guidance to conductimage-adaptive color mapping. In addition, we construct a dataset using HDRvideos in HDR10 standard, named HDRTV1K, and select five metrics to evaluatethe results of SDRTV-to-HDRTV algorithms. Furthermore, our final resultsachieve state-of-the-art performance in quantitative comparisons and visualquality. The code and dataset are available athttps://github.com/chxy95/HDRTVNet.
Code Repositories
Benchmarks
| Benchmark | Methodology | Metrics |
|---|---|---|
| inverse-tone-mapping-on-msu-hdr-video | HDRTVNet | HDR-PSNR: 35.9721 HDR-SSIM: 0.9918 HDR-VQM: 0.1296 |
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