In order to overcome the problem of large amounts of data in PIE imaging, the theory of compressive sensing is adopted for PIE imaging. Diffraction patterns are sparsified and compressed, which can reduce the amount of data requiring save. The original distribution of scattering spot can be reconstructed with subspace persuit (SP) or orthogonal matching pursuit (OMP) tuning algorithm in the retrieval process, then image reconstruction is realized using regular PIE algorithm. Simulation and experimental results show that the images can be reconstructed perfectly when the compression ratio is 30%. SP algorithm is more appropriate than OMP algorithm for PIE imaging.