Aortic pulse wave velocity (PWV) increases with arterial stiffness and aging and predicts cardiovascular mortality. It is commonly estimated using applanation tonometry at carotid and femoral arterial sites (cfPWV). Although cardiovascular MRI offers reliable segmental measurement of arterial length, accurate transit time (TT) determination between flow curves remains a challenge. We developed a wavelet-based method, which enables temporal localization of signal frequencies, to estimate TT by the weighted phase difference between ascending and descending aorta flow curves. We compared this approach in terms of linear correlations with age, cfPWV and effects of decreasing temporal resolution by factors of 2, 3 and 4, with previous methods which 1) restrict their analysis to systolic upslope (time domain upslopes-archPWVTU) and 2) decompose into harmonics flow curves from the whole cardiac cycle (Fourier-based-archPWVF-robust to low temporal resolution). We studied 71 healthy subjects (45±15 years, 29 females) who underwent MRI velocity acquisitions and cfPWV measurements. Wavelet method provided the highest linear correlations with age and cfPWV and was the most robust to low temporal resolutions. Wavelet method might help to overcome current limitations related to MRI low temporal resolution.