Optical illusion hidden picture is an interesting visual perceptual phenomenon where an image is cleverly integrated into another picture in a way that is not immediately obvious to the viewer. Established on off-the-shelf text-to-image diffusion model, we propose a novel \textbf{P}hase-\textbf{T}ransferred \textbf{Diffusion} Model (PTDiffusion) for hidden art syntheses. PTDiffusion embeds an input reference image into arbitrary scenes that are faithful to text prompts, while exhibiting hidden visual cues of the reference image. At the heart of our method is a plug-and-play phase transfer mechanism that dynamically and progressively transplants diffusion features' phase spectrum from the denoising process to reconstruct the reference image into the one to sample the illusion picture, realizing harmonious fusion of the reference structural information and the target semantic information. Furthermore, we propose an asynchronous phase transfer mechanism to flexibly control the degree of hidden image discernability. Our method is training-free, all while substantially outperforming related methods in image quality, text fidelity, visual discernibility, and contextual naturalness for illusion picture synthesis, as fully demonstrated by extensive qualitative and quantitative experiments.