We propose an on-line noise reduction system especially designed for noisy CMOS image sensors. Image sequences from CMOS sensors in general are corrupted by two types of noise, temporal noise and fixed pattern noise (FPN). It is shown how the FPN component can be estimated from a sequence. We studied the theoretical performance of two different approaches called direct and indirect FPN estimation. We show that indirect estimation gives superior performance, both theoretically and by simulations. The FPN estimates can be used to improve the image quality by compensating it. We assess the quality of the estimates by the achievable SNR gains. Using those results a dedicated filtering scheme has been designed to accomplish both temporal noise reduction and FPN correction by applying a single noise filter. It allows signal gains of up to 12dB and provides a high visual quality of the results. We further analyzed and optimized the memory size and bandwidth requirements of our scheme and conclude that it is possible to implement it in hardware. The required memory size is 288kByte and the memory access rate is 70MHz. Our algorithm allows the integration of noisy CMOS sensors with digital noise reduction and other circuitry on a system-on-chip solution.