Design of Robust Sensing Matrix for UAV Images Encryption and Compression

The sparse representation error (SRE) exists when the images are represented sparsely. SRE is particularly large in unmanned aerial vehicles (UAV) due to disturbance of harsh environment or instability its flight, which will bring more noise. In compressed sensing (CS) system, projected measurement a significant challenge recovery accuracy images. this work, new structure proposed. Following structure, lower (LSRE) achieved by eliminating groups representation. With proposed LSRE modeling, robust matrix designed compress and encrypt UAV Experiments for carried out compare performance algorithm with existing related algorithms. results reveal superior accuracy. CS framework address scenario dominant.