The early application of compressive sensing in optical imaging focuses on spatial compressive imaging. In recent years, increasing compressive imaging systems have employed detector array instead of a single detector for collecting measured values. Moreover, the scope of compressive imaging expands from two-dimensional space to three-dimensional ranging, high-speed imaging, multispectral imaging, ghost imaging, and holography imaging. Herein, we analyzed recent works on high-resolution compressive imaging, compressive sensing ranging, and temporal high-speed compressive imaging with details, summarized the research progresses of measured matrix design by combining spatial compressive imaging, works on sensing matrix design in spatial compressive imaging, discussed their challenges and future development opportunities, and reviewed the applications of compressive sensing in multispectral imaging, ghost imaging, and holography imaging. Furthermore, we summarized the improvement of reconstruction performance of system targets by applying deep learning to compressive imaging.