An improved Paik′s Boltzmann machine was presented to optimize the traditional Boltzmann method that suffers from not only being trapped into a local extreme but also a slow convergence.By proposed the method,the Paik′s algorithm is integrated into the Boltzmann machine to restored images.Then,serial models are extended to parallel models to fasten the convergence speed and a subunit step is adopted to increase calculation precision.Finally a step adaptive method is used to trade off the contradiction of convergence precision and convergence velocity.Moreover,each improvement for the origonal algorithm is expatiated by theoritical validation,convergence analysis,and discussions of residual variations.Experiments demonstrate that the proposed method can be converged to the global minimum,and the Peak Signal Noise Ratio (PSNR) of the restored image is 0.5-0.8 dB higher than that of the improved Boltzmann method proposed by Bellouquid,while the consumed time is only 1/3 that of the latter.These results show that the proposed method is effective and valid for image restorations.