A standard data set for performance analysis of advanced IR image processing techniques

Abstract

Modern IR cameras are increasingly equipped with built-in advanced (often non-linear) image and signal processing algorithms (like fusion, super-resolution, dynamic range compression etc.) which can tremendously influence performance characteristics. Traditional approaches to range performance modeling are of limited use for these types of equipment. Several groups have tried to overcome this problem by producing a variety of imagery to assess the impact of advanced signal and image processing. Mostly, this data was taken from classified targets and/ or using classified imager and is thus not suitable for comparison studies between different groups from government, industry and universities. To ameliorate this situation, NATO SET-140 has undertaken a systematic measurement campaign at the DGA technical proving ground in Angers, France, to produce an openly distributable data set suitable for the assessment of fusion, super-resolution, local contrast enhancement, dynamic range compression and image-based NUC algorithm performance. The imagery was recorded for different target / background settings, camera and/or object movements and temperature contrasts. MWIR, LWIR and Dual-band cameras were used for recording and were also thoroughly characterized in the lab. We present a selection of the data set together with examples of their use in the assessment of super-resolution and contrast enhancement algorithms. © 2012 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).