The availability of high-resolution satellite images increases with advancements in remote sensing technology. These satellite images are used in various earth observation applications such as disaster management, military applications, weather forecasting, land use and cover, and many more. Satellite images have large volumes stored in memory devices. These satellite images are transmitted to the ground station for processing and analysis. In these cases, images are vulnerable to privacy issues. As technology advances, onboard processing of satellite images using intelligent systems processes the images faster. A model such as field programmable gate arrays (FPGA) is used in onboard processing to process satellite images. However, images are susceptible to faults induced by harsh radiation environments in space. Encryption is one of the most assured methods to provide privacy to satellite images. Hence, encryption of satellite images during processing, storage, and transmission is the present rising demand. There are various encryption methods implemented using algorithms such as advanced encryption standard (AES), homomorphic, advanced encryption standard-counter (AES-CTR), and chaotic maps. Concurrent processing and encryption of images using MapReduce with Hadoop Framework perform the task faster. The focus of this paper is a comparative study of the various encryption methods used in recent years.