Elastography, computation of elasticity modulus of tissue is one of medical imaging methods with applications such as tumor detection and ablation therapy. Phase-based time delay estimation methods exploit the frequency information of the RF data to obtain strain estimates . Although iterative Phase zero estimation is more computationally efficient in comparison to methods that seek for the absolute maximum cross-correlation between precompression and postcompression echo signals, it is quite sensitive to noise. The reason for this sensitivity is that for this iterative method an initial guess for the time shift is needed for each pixel. To estimate time shifts for the sample k, the time shift resulted from iterative phase zero method applied on sample k-1 is used as an initial value. This makes the method sensitive to noise because the error is propagating sample by sample and if the method gets unstable for any pixel, it will give unstable result for the following pixels in image line. Proposed strategy in this work to overcome this problem is to first estimate the displacement using Dynamic Programming  and use the results from DP as an initial guess of displacement for each pixel in iterative Phase zero method. Recently, regularized methods that incorporate the prior of tissue continuity in time delay estimation have been shown to produce low-noise and high contrast strain images [3,5]. In this work, we also incorporate the prior of tissue motion continuity in the phase zero method to make the zero-phase method more robust to signal decorrelation.