由于全变分(total variation，TV)正则化方法能够很好地保持边界，因而在图像去噪和恢复中得到广泛的应用，但其一个显著的缺点就是会在恢复出来的图像中产生阶梯效应。针对此问题给出了一种基于四阶偏微分方程(PDE)的盲图像恢复模型，该模型在Chan和Wong的全变分模型的基础上，用四阶范数来代替TV范数，构造了一种新的能量泛函，消除了全变分正则化方法所产生的阶梯效应。实验结果表明，该模型能取得较好的图像恢复效果。

Many of the current methods for image denoising and restoration utilize total variation (TV) regularization to preserve its beneficial edge properties. However a particular caveat of TV regularization is the staircasing phenomenon in recovered images. A new blind restoration model based on a fourth order partial differential equation (PDE) is proposed for image restoration, which improved the Chan and Wongs TV model. The new method is to introduce fourth order norm into the energy function instead of TV norm, to overcoming the staircasing in reconstructions form TV regularization. The result of experiment shows that this restoration model is more visible.