Phase retrieval is an issue that tries to recover an image from its Fourier magnitude measurements. Since the Fourier magnitude measurements contain less information, the traditional phase retrieval algorithms can not reconstruct the image efficiently under the scenario that the oversampling ratio is relatively low. Therefore, how to use the suitable image priors to improve the reconstruction quality of the image is the key issue. In this paper, the cartoon-texture model is utilized for phase retrieval algorithm. Two sparse representation methods including both Total Variation (TV) and Dual-Tree Complex Wavelet Transform (DTCWT) are exploited to decompose the image into two parts, namely the cartoon component and the texture component. Moreover, Alternating Direction Method of Multipliers (ADMM) is exploited to solve the corresponding problem. The experimental results show that the proposed algorithm can effectively improve the quality of image reconstruction.
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