Modeling and image motion analysis of parallel complementary compressive sensing imaging system

Based on the theory of compressive sensing, a parallel complementary compressive sensing imaging system is proposed, and the mathematical model of block parallel processing is established. Parametric analysis shows that the quality of the restored image increases with the increase of observed compression ratio and the decrease of the number of blocks, which is in conflict with total amount of data and time-consuming of algorithm, and needs to be considered comprehensively. According to the demand of space remote sensing system applied in push-broom mode, the image motion model of the system is established. The results show that the image motion has a severe effect on the quality of restored image, and increasingly responsive with the decrease of the number of blocks. when the orbital image motion parameter is constant, improving the frame rate of the detector and increasing the pixel size can obtain a smaller image motion ratio, thereby enhancing the image quality. But the application scope of the system for push-broom imaging is somewhat limited for its significantly degrade under low image motion ratio.