Performance Assessment of Pre-processing Filters for Infrared Search and Track Applications
To enhance detection probability and to reduce false alarms, infrared imagery is pre-processed before subjecting it to detection algorithms in infrared search and track systems. Pre-processing algorithms are used to predict the complex background and then to subtract the predicted background from the original image. The difference image is passed to the detection algorithm to further distinguish between the target and the background and/ or noise more accurately. A number of pre-processing algorithms have been reported in literature, with their relative advantages and disadvantages. This paper brings out the computational complexities and simulation results of various algorithms for assessing their relative performances. Based on these parameters, statistical algorithms in general and max-min algorithms in particular, are recommended to be used for infrared search and track systems.
Defence Science Journal, 2011, 61(3), pp.251-256, DOI:http://dx.doi.org/10.14429/dsj.61.60
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