Registration method for infrared images under conditions of fixed-pattern noise

This paper proposes a new registration method for infrared images under conditions of fixed-pattern noise (FPN). Conventional registration techniques are susceptible to FPN and it is therefore very desirable to have a registration algorithm that is tolerant to FPN. For this purpose, we utilize the difference of the cross-power spectrum of two discrete shifted images to suppress the noise power spectrum while the shifts information is well preserved. In particular, we show that the phase of the cross-power spectrum difference is a periodic two-dimensional binary stripe signal with the exact shifts determined to subpixel accuracy by the number of periods of the phase difference along each frequency axis. Robust estimates of shifts can be obtained by transforming its discontinuities to Hough domain. Experimental results show that the proposed method exhibits robust and accurate registration performance even for the noisy images that could not be handled by conventional registration algorithms. We have also incorporated this technique to a registration-based nonuniformity correction (NUC) framework, indicating that our registration technique is able to estimate motion parameters reliably, leading to satisfactory NUC result. ► We propose a registration method for infrared images corrupted by fixed-pattern noise. ► The noise power spectrum is eliminated in the difference of the cross-power spectrum. ► The phase matrix of the difference is a 2D binary tripe signal. ► The period of the square signal along each axis determines the corresponding shifts. ► Robust estimates of shifts can be performed in the Hough-transform domain.