A nonlinear partial differential equation model based on nonlocal information was proposed to remove noise and preserve the edges.

针对传统扩散模型中的边界模糊问题，提出一种基于非局部信息的非线性偏微分方程去噪模型。

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To avoid multicollinearity's disturbance, partial least-squares regression which can identify system information and noise is introduced to model, and a program is compiled.

为了克服多重相关性对模型的干扰，引入了能辨别系统信息与噪声的偏最小二乘回归，并编制了程序。

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Second, we add fringe restraint in the model of partial grey level, so that the points with stronger fringe information could have more possibility to become the perfect candidate points.

第二，我们在局部灰度模型中加入了边缘约束，使边缘信息较强的点有更大的可能成为最佳候选点。

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