Using the maximum of twodimensional wavelet transform coefficient modulus as wavelet ridge will produce large error for the fringe image with noise interference. In view of this problem, wavelet ridge extraction algorithm utilizing a cost function in twodimensional wavelet transform is proposed. Firstly, the maximum point is extracted from twodimensional wavelet transform coefficient modulus, and the local maximum points exceeded 90% of maximum point are also obtained, these points are selected as wavelet ridge candidates. Then, the gradient of scale factor is introduced into the modulus, the cost function is established to evaluate the value of all candidate points. The logarithmic Logistic model is used to adjust the weights to improve the estimator. Finally, the dynamic programming is applied to accurately identify the optimal wavelet ridge, and the wrapped phase can be obtained by extracting the phase at the ridge. Consequently, the fringe pattern with low signaltonoise ratio can be demodulated accurately, and its noise immunity is better than wavelet ridge extraction from direct maximum modulus. At the same time, only one fringe pattern can be projected to reconstruct the shape of object, which can be used for dynamic 3D measurement in harsh environment. Simulation and experimental results show that, for the fringe pattern with noise, the accuracy of 3D surface recovery by the proposed algorithm is increased, compared with the maximum modulus of the wavelet ridge extraction algorithm. And the computation time is shortened by 46.9% compared with the extraction of the whole local extreme points. In addition, , simulation results show that the 2D Cauchy wavelet has better directivity and higher accuracy by applying different mother wavelets to the proposed method.