Quantitative analysis of infrared contrast enhancement algorithms

Seth Weith-Glushko; Carl Salvaggio

doi:10.1117/12.720092

30 April 2007 Quantitative analysis of infrared contrast enhancement algorithms

Seth Weith-Glushko, Carl Salvaggio

Proceedings Volume 6543, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XVIII; 65430S (2007) https://doi.org/10.1117/12.720092
Event: Defense and Security Symposium, 2007, Orlando, Florida, United States

Abstract

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.

Citation Download Citation

Seth Weith-Glushko and Carl Salvaggio "Quantitative analysis of infrared contrast enhancement algorithms", Proc. SPIE 6543, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XVIII, 65430S (30 April 2007); https://doi.org/10.1117/12.720092

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