Estimation of Zero-Frequency Noise Power Density in Digital Imaging

Noise power spectrum (NPS) at zero frequency can efficiently represent noise properties of imaging systems. However, estimations of zero-frequency NPS are susceptible to distortion due to several factors leading to low-estimate precisions. In this letter, a high-precision estimate algorithm for zero-frequency NPS is proposed. The proposed estimate is a compensated sum of signal variances and covariances. The accuracy and precision of the proposed approach were first observed with synthetic data. A flat panel radiography detector based on CsI(TI)-scintillator was then used to experimentally observe the improved estimate precision of the proposed algorithm. Experiment results showed that the estimation precision was improved to 14 times compared to that of the conventional method.