摘要： Based on the theories of single pixel camera and compressed sensing image reconstruction, the sparse basis, the projection method of measurement matrix and the signal reconstruction algorithm are optimized. Firstly, for the sparse representation of image, the restraint matrix is designed combining the characteristics of wavelet sparse coefficients to enhance the sparse representation ability of the discrete wavelet base, which improves the quality of image reconstruction and imaging by single pixel camera. Then in the single pixel camera system, the projection method is improved according to the characteristics of the DMD micro-mirror, and a new bilateral projection method based on the block diagonal measurement matrix is proposed to realize the super resolution imaging of the outdoor scene, reducing the number of measurement and improving the imaging quality. Finally, for the algorithm of image reconstruction, combining the characteristics of convex optimization and non-convex optimization algorithms, a new algorithm from convex optimization approximately to non convex optimization algorithm is proposed, and compared with traditional image reconstruction algorithm such as greedy pursuit algorithm, minimum norm algorithm and image interpolation, the peak signal to noise ratio (PSNR) and imaging quality of reconstructed images are effectively improved. The feasibility of the proposed methods is demonstrated by simulation experiments and imaging experiments of single pixel camera.