An Anti-interfering Reconstruction Algorithm Based on Compressed Sensing

When images compressed by traditional transformation-based compression algorithms are transmitted over wireless channels, if the gaussian random interference causes the loss of the crucial transformation coefficients, the contents of the reconstructed images will be lost obviously and this will reduce the accuracy of the subsequent detection and recognition results greatly. In order to solve this problem, this paper proposed an antiinterfering image reconstruction algorithm based on compressed sensing. This algorithm first confirmed the new compressed sensing signals and the new reconstruction matrix based on the locations of the compressed sensing signal components corresponding to the gaussian-interfered bit stream, and then reconstructed the original images employing the iterative threshold algorithm. The simulation results demonstrated that the new algorithm reconstructed exact images at low bit error rates, and reconstructed inexact images whose qualities were slightly lowered without loss of local contents at high bit error rates. As a result, our algorithm is able to overcome the deficiencies of compression algorithms based on diverse transformations and the iterative threshold algorithm, thus proposes a feasible solution scheme for the anti-interfering problem that arises in wireless image transmission