A 1/f noise optimized correlated multiple sampling technique for complementary metal oxide semiconductor image sensor

Abstract

SummaryCorrelated multiple sampling (CMS) technique is often used to reduce random noise in complementary metal oxide semiconductor (CMOS) image sensor, but as the number of samples increases, the suppression of 1/f noise by standard CMS based on averaging sampling gradually decreases. Therefore, in this paper, a 1/f noise optimized correlated multiple sampling (NOCMS) technique based on differentiated sampling weights is proposed. Transfer functions of standard CMS and NOCMS for analyzing the suppression effect of random noise respectively are derived based on the Fourier transform theory. And NOCMS shows a dramatic advantage in the suppression of 1/f noise. In addition, a circuit structure based on single‐slope analog‐to‐digital converter (SSADC) for implementing NOCMS is suggested. Ramp generator provides multiple sets of ramps with different slopes to quantify the reset and signal voltages of pixel output. Sampling weights are increased with the decrease of ramp slopes. The last reset and first signal values are weighted more due to their potentially higher correlations which highlights the principle of assigning weights. Simulation results under 110 nm CMOS technology illustrate that the input‐referred random noise is 142.9 V under standard CMS and 120.9 V under NOCMS when the number of samples equals 8. The noise reduction effect is improved by 15%. NOCMS makes it possible to further reduce 1/f noise of CMOS image sensor.