强噪声背景下的图像复原对于改善目标图像的视觉效果，提高后续图像分析或处理的性能起着关键性作用。首先研究双稳态非线性系统的随机共振非周期响应；然后通过多方向Hilbert扫描法，在保持图像像素空间相关性的基础上，将2维灰度图像转换为多个1维非周期信号序列；最后利用双稳态系统、图像信号以及噪声之间的随机共振协同作用，实现强噪声背景灰度图像的复原。实验结果表明，随机共振复原方法在较好地重现图像细节的同时，能有效抑制图像中的噪声；尤其在低信噪比情形下，本文方法在信噪比改善程度与灰度层次感上，要明显优于传统图像复原方法。

The restoration of the image with strong noise has been playing a key role in improving the visual effects of the image, furthermore, enhancing the performance of the image analysis or processing. This paper studied the aperiodic response of the stochastic resonance in the bistable nonlinear system. Then, by using of the multi-directional Hilbert scanning method, the two-dimensional gray image was converted to several one-dimensional and aperiodic signal sequences, which maintained the space correlation of the image pixels. Finally, the restoration of the gray image with strong noise was achieved by using the stochastic resonance synergy of the bistable system image signals and noise. The experimental results showed that the image restoration method based on the stochastic resonance could effectively suppress the noise and make the image recurrent well in detail. Especially in the low SNR cases, this method was obviously superior to the traditional methods of image restoration in the aspects of the SNR improvement and gray hierarchy.