Abstract:

According to the property that for Gaussian signals only, all cumulant spectra of order greater than two are identically zero, a High-Order-Statistics based Nonuniformity Correction(HOS-NUC) approach is taken for the adaptive estimation of the gain and bias nonuniformity in infrared focal-plane array sensors from scene data. The proposed algorithm consists of two main parts: the first part involves a periodic statistical estimation of the model parameters using the moment and cumulant; the second part involves the estimated parameters in restoring the true image by a winner filter. The proposed method has been tested with video sequences of simulated infrared data, reducing the fixed pattern noise and reaching high correction levels.

Key words: High-Order-Statistics, infrared focal plane array, non-uniformity correction, fixed-pattern noise