Dynamic range reduction and contrast enhancement are two image-processing methods that are required when
developing thermal camera systems. The two methods must be performed in such a way that the high dynamic range
imagery output from current sensors are compressed in a pleasing way for display on lower dynamic range monitors.
This research examines a quantitative analysis of infrared contrast enhancement algorithms found in literature and
developed by the author. Four algorithms were studied, three of which were found in literature and one developed by
the author: tail-less plateau equalization (TPE), adaptive plateau equalization (APE), the method according to Aare
Mällo (MEAM), and infrared multi-scale retinex (IMSR). TPE and APE are histogram-based methods, requiring the
calculation of the probability density of digital counts within an image. MEAM and IMSR are frequency-domain
methods, methods that operate on input imagery that has been split into components containing differing spatial
frequency content. After a rate of growth analysis and psychophysical trial were performed, MEAM was found to be the
best algorithm.
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