As a new information acquisition theory, compressive sensing (CS) has important significance in image processing. The decoding algorithm of error correction codes can be used for CS sparse signal reconstruction because of their same essence. This paper first constructs scale-free network irregular low density parity check (LDPC) codes by using the properties of power law distribution and the shortest path between nodes of scale-free networks; then takes the LDPC codes as sensing matrix, giving

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... CS processing method based on scale-free network irregular LDPC codes; at last, gives reconstruction of original sparse signal via belief propagation (BP) decoding algorithm. The simulation results verify the effectiveness of the algorithm by making comparison with different signal models.