Noise Power Spectrum Estimation of Column Fixed Pattern Noise in CMOS Image Sensors Based on AR Model

Abstract

CMOS image sensors are extensively utilized in digital imaging systems for their excellent performance and low power consumption. As an essential components in the system, CMOS image sensors are expected with low noise levels. The images captured by CMOS image sensor contain random noise (RN), digital noise (DN), and fixed pattern noise (FPN). FPN of CMOS image sensors has a greater impact on the perceived image quality than random noise, which seriously restricts the development and application of CMOS image sensors. This paper proposed a noise power spectrum (NPS) method for estimating column FPN of CMOS image sensor based on AR model. First, dozens of images under uniform illumination are acquired by established test vehicle. Second, random noise of the images is restrained by using the multi-frame averaging method. Then, column FPN is modeled by an autoregressive (AR) random process subsequently. Ultimately, column FPN is estimated by calculating NPS of the image based on the AR model. A case application was proposed by using this method.