An adaptive mean frequency estimator is proposed for color flow imaging. It is based on a series expansion of the first derivative of the autocorrelation function of the Doppler signal at origin. Its bias can be reduced by shifting the integration bounds in the series expansion and its variance adjusted by adapting the coefficients of the serial development. This estimator can be fitted to the specific characteristics of the clutter rejection filter using the signal-to-noise ratio (SNR) of the Doppler signal as an adaptive parameter. Its performance is compared to that of the usual correlation angle estimator, and its thresholded version, as well as that of the general mean frequency estimator, using a model of Doppler signal. The detection of low frequencies was significantly improved. The mean square error (MSE) was reduced an average 15 fold over a 25-dB range on the SNR, compared to the correlation angle estimator (CAE) or the general mean frequency estimator. A two-fold reduction in the MSE was obtained compared to the thresholded correlation angle estimator.