Sensing in the Shortwave Infrared (SWIR) range has only recently been made practical. The SWIR
band has an important advantage – it is not visible to the human eye, but since it is reflective,
shows shadows and contrast in its imagery. Moreover, SWIR sensors are highly tolerant to
challenging atmospheric conditions such as fog and smoke. They can be made extremely sensitive,
thus can work in very dark conditions. However, fundamental differences exist in the appearance
between images sensed in visible and SWIR bands. In particular, human faces in SWIR images do
not match human intuition and make it difficult to recognize familiar faces by looking at such images.
Only few previous works in the literature consider the difference in appearance between visible and
SWIR images. These works deal with extraction of band-invariant features from images but they do not
try to map the tones of a SWIR image to the tones of its counterpart visible image. In this project,
we deal with a novel tone mapping application for SWIR face images. We propose a method to map
the tones of a human face acquired in the SWIR band to make it more similar to its appearance in the
visible band. The proposed technique is easy to implement and produces natural looking face images.