The invention discloses an effective '0,1' sparse
signal compressed sensing reconstruction method. The method mainly comprises a sparse and uniform measurement matrix construction part and an iteration reconstruction order part based on a
bipartite graph. According to the method, a
bipartite graph model in a
graph theory is ingeniously introduced, the minimum cover characteristic of the
bipartite graph is closely combined, a constraint condition is appropriately added, and the sparse, uniform and minimally-covered measurement matrix is constructed. Based on the special structure that the '0,1' sparse signals are fully utilized in an iteration
reconstruction algorithm based on the bipartite, the connecting line phi ij of the bipartite graph is deleted and a measurement value y is updated through an iteration method, and an original
signal reconstruction method is achieved finally. According to the method, the bipartite
graph model in the
graph theory is introduced in
compressed sensing sampling and reconstruction, compared with an l1
norm minimization method, reconstruction errors do not exist, the method can be applied to compressive sampling of
neutron pulse sequences, earthquake signals,
wireless sensor networks, binary images and the like.