The evaluation of CMOS sensors performance in terms of color accuracy and noise is a big challenge for camera phone manufacturers. On this paper, we present a tool developed with Matlab at STMicroelectronics which allows quality parameters to be evaluated on simulated images. These images are computed based on measured or predicted Quantum Efficiency (QE) curves and noise model. By setting the parameters of integration time and illumination, the tool optimizes the color correction matrix (CCM) and calculates the color error, color saturation and signal-to-noise ratio (SNR). After this color correction optimization step, a Graphics User Interface (GUI) has been designed to display a simulated image at a chosen illumination level, with all the characteristics of a real image taken by the sensor with the previous color correction. Simulated images can be a synthetic Macbeth ColorChecker, for which reflectance of each patch is known, or a multi-spectral image, described by the reflectance spectrum of each pixel or an image taken at high-light level. A validation of the results has been performed with ST under development sensors. Finally we present two applications one based on the trade-offs between color saturation and noise by optimizing the CCM and the other based on demosaicking SNR trade-offs.© (2010) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.