分析了遥感图像获取过程中导致图像退化模糊的原因。讨论了一种借助图像中的特定线状目标信息(如桥梁、堤坝等)，采用经验拟合的方式提取图像获取、传输过程中的点扩散函数，并利用该点扩散函数结合频域维纳滤波器求解去图像模糊的空域反卷积算子。将该方法应用于中巴资源卫星一号(CBERS-1)图像，图像质量得到明显的提高，收到了较好的复原效果。

The integrating effect of the Point Spread Function (PSF) of a satellite remote sensing system significantly blurred the acquired image and reduced the spatial resolution of the data. This paper firstly analyzed the main factors which result in the image blur. We then discussed the derivative of Linear Spread Function (LSF) by the use of linear step structures that are recorded in the image. The PSF of an image can be approximated by interpolating two linearly separable orthogonal LSFs. Deconvolution filters are derived specifically for each image from its PSF using a Weiner filter in the frequency domain and applying an invert Fourier transform to convert into space domain. The use of Wiener filter could guarantee the achievement of the cleared image while reducing the noise influence. Finally, the deconvolution filters were applied in the 3rd channel of a full scene CBERS 1 image so that it can restore the original signal.A significant improvement of the image quality was achieved.