Perception-inspired Tone Mapping

mapping algorithm to depict their original appearance on existing
display devices whose capabilities in terms of dynamic range are
insufficient. The insightful application of knowledge about human
visual system can assure high fidelity of depiction in such an
algorithm.

In this thesis, we design new tone mapping models and improve existing
algorithms by an informed use of human perception to provide a high
fidelity depiction of high dynamic range. We develop a real-time tone
mapping solution which reproduces the subjective appearance of dynamic
HDR contents by accounting for perceptual effects that significantly
contribute to the appearance of natural scenes. We design a
computational model of lightness perception that can be applied to
high quality tone mapping for static images to reproduce their
original HDR appearance in terms of lightness. We identify common
distortions typical to tone mapping which may hinder the comprehension
of image contents, we design appropriate metrics to measure the
perceived magnitude of these distortions and evaluate existing tone
mapping algorithms accordingly. To compensate for observed
distortions, we introduce a method which improves the tone mapping
results beyond numerically optimized solution by using techniques
strongly based on perception of contrasts. Presented solutions can be
efficiently integrated in varied HDR applications including
photography, playback of HDR video, image synthesis, light
simulations, predictive rendering, and computer games.