Using lensless imaging based on Fresnel aperture coding,low-cost and lightweight incoherent optical imaging systems are constructed,which improves the possibility of becoming an everyday application.However,it still suffers from poor image reconstruction quality due to the difference in gradient domain sparsity between the twin image and the original image in the reconstructed imageIn order to improve the imaging quality,this paper proposes to use the augmented Lagrangian function method and the alternating direction method based on total variational regularization to realize the reconstruction of Fresnel aperture-coded lensless imaging.The experimental results show that the algorithm we use improves the quality of the reconstructed image and also recovers more sharp details of the image compared to the two-step iterative shrinkage/thresholding algorithm (TwIST).