Image reconstruction from the measurements of the image Fourier transform magnitude remains an important and difficult problem. Among all the approaches developed to solve this problem, the iterative transform algorithms are currently the most efficient. However, these algorithms suffer from major drawbacks that limit their practical application. We introduce a wavelet adaptation of the general iterative algorithm that can significantly improve the performance of the algorithm while dramatically reducing its computational complexity.