  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.
