提出一种新的图像局部模糊检测方法，并将其应用于篡改图像的检测.该方法基于最小二乘估计来计算图像中每个像素的估计误差，再将每个像素和其周围像素估计误差的方差作为模糊特征，然后利用频域的相关系数确定一置信区间，并根据该区间模糊特征的概率分布特性动态确定阈值，进而分离出模糊区域内的像素.实验结果表明，该方法能获得更高的检测正确率和分离精度.

A novel approach of regional blur identification is proposed and applied to image forgery detection. Based on least-square (LS) estimation, prediction error of each pixel is calculated. Variance of the prediction errors of a pixel and its neighborhood is regarded as the blur characteristic of the pixel. A threshold is determined dynamically according to the distribution of correlation coefficient in the frequency domain and blur characteristic in the spatial domain. Thus pixels in a blurred area are discriminated from sharp pixels. Experimental results show that the proposed method has a high accuracy rate in blur region detection.