Significance   Laser imaging refers to an imaging method that emits a specially designed laser signal, receives the laser echo, and processes it to obtain attribute information such as an image of the target. Laser imaging has wide applications in target detection, satellite surveying, smart agriculture, national defense and aerospace, and other fields. It contains a series of signals and information processing processes, including denoising, radiation, geometric correction, point cloud processing of laser echo signals, and subsequent data processing of various imaging tasks (such as laser ranging, laser image reconstruction, target detection, etc.), and have a critical impact on imaging quality and play a crucial role in the application of imaging information. Currently, with the continuous development of imaging systems and imaging hardware, laser imaging processing technology has increasingly high requirements for processing accuracy and speed, and involves a wider range of technical fields. Especially with the rapid development of machine learning technology represented by deep learning, it has achieved better results than traditional technologies in many classic problems, and has also been successfully applied in laser imaging processing technology, providing a new development direction for laser imaging processing.

  Progress  This paper first introduces the characteristics of laser imaging processing technology of typical imaging system (Fig.1). We explained the characteristics of imaging processing technologies under various laser imaging systems, identified the similarities and differences between laser imaging processing technologies under different systems, and conducted a comparative analysis of laser imaging processing technologies under typical imaging systems (Tab.1). In summary, it can be found that although there are differences in the names of signal and information processing contents corresponding to different systems, the common contents of laser imaging signal processing can be summarized into four aspects of signal denoising, radiation correction, geometric correction, and point cloud processing. The common contents of imaging information processing can be summarized into three common processing contents of laser ranging, image reconstruction, and object detection. 　　Based on the summarized common methods of laser imaging signals and information processing technology, we conducted separate studies. In the current research status of laser imaging signal processing technology, we focus on the laser signal denoising, correction and laser point cloud processing technology. In the research of signal denoising, we have conducted research based on wavelet transform, empirical mode decomposition, variational mode decomposition, and hybrid methods. We have also conducted specialized research on the application of deep learning algorithms in laser signal denoising. Representative algorithms are shown (Fig.5). The laser signal correction focuses on two aspects of laser signal radiation and geometric correction. And in point cloud signal processing, we mainly summarized the work on denoising and background removal, and focused on the work based on deep learning. Besides, we have organized and summarized the research on laser information processing for laser ranging, image reconstruction and target detection information processing technology. In the section of laser image reconstruction, we conducted research on three aspects of stereo matching, point cloud data stitching, and laser reflection tomography reconstruction. In object detection, the traditional method and deep-learning based method were elaborated, and classic point cloud object detection algorithms based on deep learning algorithms were studied (Fig.9-10). 　　Based on the classification of laser imaging processing technology in this paper, we finally analyzed the current challenges and future development directions of laser imaging processing technologies, and summarized the current development of laser imaging technology and future laser imaging processing technology examples. It is hoped that it can provide some reference for the research related to laser imaging.

  Conclusions and Prospects  Laser imaging has always been a hot topic in the field of optical imaging and signal processing. In the past 20 years, laser imaging signal and information processing technology has made great progress. In the previous studies, deep learning has been deeply applied to laser imaging processing. Through the powerful representation learning ability of deep learning, great improvements have been made in laser imaging processing quality, precision, robustness and other aspects. In the future research on different signal and information processing tasks, the standardization of large-scale data sets for imaging tasks and more robust deep neural network processing paradigm will be the further development direction of the research. It should be noted that laser imaging processing technology is not limited to the contents in this paper. There are many other signal and information processing technologies not involved in this paper, which worth further study and exploration by researchers.