Redistributing the Precision and Content in 3D-LUT-based Inverse Tone-mapping for HDR/WCG Display

Cheng Guo, Leidong Fan, Qian Zhang, Hanyuan Liu, Kanglin Liu +1 more
9/29/2023
cs.MMcs.CV

Official code: AndreGuo/ITMLUT (63 stars, MPL-2.0, last commit 2024-05-11).

Abstract

ITM(inverse tone-mapping) converts SDR (standard dynamic range) footage to HDR/WCG (high dynamic range /wide color gamut) for media production. It happens not only when remastering legacy SDR footage in front-end content provider, but also adapting on-theair SDR service on user-end HDR display. The latter requires more efficiency, thus the pre-calculated LUT (look-up table) has become a popular solution. Yet, conventional fixed LUT lacks adaptability, so we learn from research community and combine it with AI. Meanwhile, higher-bit-depth HDR/WCG requires larger LUT than SDR, so we consult traditional ITM for an efficiency-performance trade-off: We use 3 smaller LUTs, each has a non-uniform packing (precision) respectively denser in dark, middle and bright luma range. In this case, their results will have less error only in their own range, so we use a contribution map to combine their best parts to final result. With the guidance of this map, the elements (content) of 3 LUTs will also be redistributed during training. We conduct ablation studies to verify method's effectiveness, and subjective and objective experiments to show its practicability. Code is available at: https://github.com/AndreGuo/ITMLUT.

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Code Implementations(1)

AndreGuo/ITMLUTOfficial100%
MPL-2.0

Official PyTorch implementation of "Redistributing the Precision and Content in 3D-LUT-based Inverse Tone-mapping for HDR/WCG Display" in CVMP2023 (SIGGRAPH European Conference on Visual Media Production).

633C++, CudaSep 27, 20232 years agoMPL-2.0

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Cite this paper

@article{guo2023redistributing,
  title  = {Redistributing the Precision and Content in 3D-LUT-based Inverse Tone-mapping for HDR/WCG Display},
  author = {Cheng Guo and Leidong Fan and Qian Zhang and Hanyuan Liu and Kanglin Liu and Xiuhua Jiang},
  year   = {2023},
  eprint = {2309.17160},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2309.17160v2}
}

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