In the intelligent era, optical perception serves as a fundamental modality for information acquisition and processing, playing a pivotal role in enabling machines to interpret the physical world. Leveraging advanced camera systems, sensors, and data processing technologies, optical systems transform rich real-world scenes into digital signals. These signals are then subjected to feature extraction via artificial intelligence algorithms to facilitate decision-making. With the proliferation of visual tasks, sensing systems have undergone continuous advancements in comprehensive performance. Among these innovations, coded optical imaging and optical pre-sensing computing, rooted in optical encoding technologies, have emerged as transformative tools in optical perception systems. These techniques not only enhance the quality of signal acquisition but also optimize system architectures, thereby boosting operational efficiency and reducing computational power consumption. This paper begins by outlining the workflow of optical perception, then delves into the revolutionary roles of optical encoding and optical computing in advancing perception technologies. It focuses on the research progress of coded optical imaging and optical pre-sensing computing, and concludes with prospects for future development opportunities and challenges in this dynamic field.