Redistributing the Precision and Content in 3D-LUT-based Inverse Tone-mapping for HDR/WCG Display
This addresses the need for efficient, adaptable ITM for media production and user-end HDR display adaptation, though it appears incremental as it builds on existing LUT and AI approaches.
The paper tackles the problem of efficiently converting SDR footage to HDR/WCG displays using inverse tone-mapping, particularly for on-the-air adaptation, by proposing a method that uses three smaller, non-uniformly packed 3D LUTs with a contribution map to combine their best parts, achieving reduced error and demonstrating effectiveness through ablation studies and experiments.
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.