Wavelets are suitable for analyzing non-stationary signals because of their good localized capabilities in both space domain and frequency domain. In traditional wavelet transform profilometry, the scaling of the mother wavelet, which moves the center frequency of the daughter wavelet, can be used to meet local signals for acquiring phase information. It is not accurate enough to extract the local phase information just changing the scale of the complex Morlet wavelet in the local position. To solve this problem, we discuss the characteristics of complex Morlet wavelets with different Gaussian window widths in fringe analysis and propose an improved wavelet processing method. The phase reconstruction results of the proposed method was compared with those of the wavelet processing by employing a cost function. The results show that the proposed method combines merits of the complex Morlet wavelets with different Gaussian window widths, which gives more reliable ridge information. The measurement accuracy of the wavelet transform profilometry is improved by employing optimized wavelet ridge extraction technique because it has stronger noise suppression ability in fringe analysis. The validity of the proposed method is verified by computer simulations and experiments.