The precise noise modeling of complementary metal oxide semiconductor image sensor (CMOS image sensor: CIS) is a significant key in understanding the noise source mechanisms, optimizing sensor design, designing noise reduction circuit, and enhancing image quality. Therefore, this paper presents an accurate random telegraph signal (RTS) noise analysis model and a novel quantitative evaluation method in motion picture for the visual sensory evaluation of CIS. In this paper, two main works will be introduced. One is that the exposure process of a video camera is simulated, in which a Gaussian noise and an RTS noise in pinned-photodiode CMOS pixels are modeled in time domain and spatial domain; the other is that a new video quality evaluation method for RTS noise is proposed. Simulation results obtained reveal that the proposed noise modeling for CIS can approximate its physical process and the proposed video quality evaluation method for RTS noise performs effectively as compared to other evaluation methods. Based on the experimental results, conclusions on how the spatial distribution of an RTS noise affects the quality of motion picture are carried out.

As the gate area decreases to the order of a square micron, individual trapping events can be detected as fluctuations between discrete levels of the drain current, known as random telegraph signal (RTS) noise. Many circuit application areas such as CMOS Image sensor and flash memory are already suffering from RTS noise. Especially, in case of flash memory, FN stress causes threshold voltage shift problems due to generation of additional oxide traps, which degrades circuit performance. In this paper, we investigated how FN stress effects on RTS noise behavior in MOSFET and monitored it in both the time domain and frequency domain.