The advancement of aerospace remote sensing technology is one of the key indicators to measure a country’s space technology capability. This technology plays an irreplaceable role in various fields such as meteorological forecasting, agricultural production, and emergency response. However, remote sensing images often contain a large amount of sensitive information, which faces serious security threats during transmission and storage. In recent years, with the increasing global investment in remote sensing research, more and more high-performance remote sensing satellites have been successfully launched. Remote sensing data has seen continuous improvements in spatial resolution, spectral resolution, and temporal resolution, leading to an exponential growth in the volume of data collected. Traditional encryption algorithms have become inadequate to meet the encryption needs of current remote sensing data. This is because traditional encryption algorithms face problems such as limited key space, weak resistance to brute-force attacks, and poor adaptability to complex data structures when processing large-scale, multi-band remote sensing data. To address these shortcomings, this paper proposes a novel encryption framework based on dynamic algorithms, and improves traditional encryption algorithms within this framework to handle multidimensional information. This significantly expands the key space while maintaining low computational overhead, and effectively supports the secure encryption of remote sensing images and videos. This research provides an efficient and scalable optical encryption strategy for the security protection of remote sensing data and lays a theoretical foundation for the encryption applications of future multi-source remote sensing data, including hyperspectral and infrared data.