Abstract: The background estimation approach using a small
window median filter is presented on the bases of analyzing IR point
target, noise and clutter model. After simplifying the two-dimensional
filter, a simple method of adopting one-dimensional median filter is
illustrated to make estimations of background according to the
characteristics of IR scanning system. The adaptive threshold is used
to segment canceled image in the background. Experimental results
show that the algorithm achieved good performance and satisfy the
requirement of big size image-s real-time processing.
Abstract: Infrared focal plane arrays (IRFPA) sensors, due to
their high sensitivity, high frame frequency and simple structure, have
become the most prominently used detectors in military applications.
However, they suffer from a common problem called the fixed pattern
noise (FPN), which severely degrades image quality and limits the
infrared imaging applications. Therefore, it is necessary to perform
non-uniformity correction (NUC) on IR image. The algorithms of
non-uniformity correction are classified into two main categories, the
calibration-based and scene-based algorithms. There exist some
shortcomings in both algorithms, hence a novel non-uniformity
correction algorithm based on non-linear fit is proposed, which
combines the advantages of the two algorithms. Experimental results
show that the proposed algorithm acquires a good effect of NUC with
a lower non-uniformity ratio.