  Thermal cameras and thermal point detectors are used to measure the
temperature of human skin. These are important devices that are used everyday
in clinical and mass screening settings, particularly in an epidemic.
Unfortunately, despite the wide use of thermal sensors, the temperature
estimates from thermal sensors do not work well in uncontrolled scene
conditions. Previous work has studied the effect of wind and other environment
factors on skin temperature, but has not considered the heating effect from
sunlight, which is termed solar loading. Existing device manufacturers
recommend that a subject who has been outdoors in sun re-acclimate to an indoor
environment after a waiting period. The waiting period, up to 30 minutes, is
insufficient for a rapid screening tool. Moreover, the error bias from solar
loading is greater for darker skin tones since melanin absorbs solar radiation.
This paper explores two approaches to address this problem. The first approach
uses transient behavior of cooling to more quickly extrapolate the steady state
temperature. A second approach explores the spatial modulation of solar
loading, to propose single-shot correction with a wide-field thermal camera. A
real world dataset comprising of thermal point, thermal image, subjective, and
objective measurements of melanin is collected with statistical significance
for the effect size observed. The single-shot correction scheme is shown to
eliminate solar loading bias in the time of a typical frame exposure (33ms).
