Abstract: The BCS-SPL algorithm, which combines the Wiener filter with PL compressive sensing signal recover algorithm, can overcome the blocking artifacts but its convergence speed is slow. To overcome the slow convergence speed of the BCS-SPL algorithm, especially on small measure rate, the BCS-SPL algorithm is combined with smooth L0 norm compressive sensing signal recovery algorithm, and a BCS-SSL0PL algorithm is proposed, which can speed up the image compressive sensing. The performance of the BCS-SSL0PL algorithm was compared with the BCS-SPL algorithm in terms of recover image quality, recover time and iteration times. Results show that the proposed BCS-SSL0PL algorithm surpasses the BCS-SPL algorithm that it can achieve the same recover quality with less time; it needs nearly the same time for different measure rate conditions; furthermore, it can improve the blocking artifacts on small measure rate conditions.