  This paper reviews the challenge on constrained high dynamic range (HDR)
imaging that was part of the New Trends in Image Restoration and Enhancement
(NTIRE) workshop, held in conjunction with CVPR 2022. This manuscript focuses
on the competition set-up, datasets, the proposed methods and their results.
The challenge aims at estimating an HDR image from multiple respective low
dynamic range (LDR) observations, which might suffer from under- or
over-exposed regions and different sources of noise. The challenge is composed
of two tracks with an emphasis on fidelity and complexity constraints: In Track
1, participants are asked to optimize objective fidelity scores while imposing
a low-complexity constraint (i.e. solutions can not exceed a given number of
operations). In Track 2, participants are asked to minimize the complexity of
their solutions while imposing a constraint on fidelity scores (i.e. solutions
are required to obtain a higher fidelity score than the prescribed baseline).
Both tracks use the same data and metrics: Fidelity is measured by means of
PSNR with respect to a ground-truth HDR image (computed both directly and with
a canonical tonemapping operation), while complexity metrics include the number
of Multiply-Accumulate (MAC) operations and runtime (in seconds).
