Based on it, the local texture model is used to adjust every points accurate location.
在此基础上利用局部纹理模型，实现了对特征点位置的进一步准确调整。
In order to more effectively make use of local features to restore the noise-infected image, a nonlinear filtering algorithm based on local texture direction probability statistic model was proposed.
为了更有效地利用图像的局部特征恢复被噪声感染的图像，基于图像局部纹理方向概率统计模型，提出一种针对混合噪声的非线性滤波算法。
Removal model based on local variance normalized can remove noise significantly in flat area but slowly and maintains the texture details poorly.
基于局部归一化的局部方差去噪模型在平坦区域去噪明显，但去噪速度慢，而且纹理细节保护欠佳。
Removal model based on local variance normalized can remove noise significantly in flat area but slowly and maintains the texture details poorly.
基于局部归一化的局部方差去噪模型在平坦区域去噪明显，但去噪速度慢，而且纹理细节保护欠佳。
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