In order to suppress the speckle noise of reconstructed image in digital holography effectively and to further improve the quality of reconstructed image, a speckle noise suppression method of reconstructed image in digital holography based on dual-tree complex wavelet transform (DT-CWT) and anisotropic diffusion is proposed. The reconstructed image is decomposed through DT-CWT. Then, the low-frequency components and the high-frequency components in six directions are processed through P_Laplace diffusion and Laplacian pyramid-based nonlinear diffusion (LPND), respectively. The new reconstructed image is synthesized through inverse dual-tree complex wavelet transform (IDT-CWT). The experimental results are given, and a subjective visual comparison is made with the method of wavelet threshold shrinkage and total variation (TV) diffusion, the method of LPND, and the method combining contourlet transform with TV and adaptive contrast diffusion. While the results are evaluated quantitatively according to peak signal to noise ratio (PSNR), correlation coefficient (COR) and running time. Experimental results show that the proposed method has a better performance in speckle noise suppression and preserves the detail and textural features of original reconstructed image more efficiently.