With the rapid development of high-throughput imaging technology, high-throughput screening technology needs more and more attention from researchers. This chapter focuses on a variety of advanced data processing and screening methods. These methods improve image quality and resolution, and are essential for effectively processing typical large amounts of data in high-throughput environments. It pays special attention to the support constraints in phase retrieval algorithms, and the application of classical algorithms and deep learning in correlation imaging and single-pixel imaging, indicating their effectiveness in improving the accuracy and speed of data screening in imaging applications.