摘要
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.
出处
《上海大学学报（自然科学版）》
CAS
CSCD
北大核心
2011年第5期586-590,共5页
Journal of Shanghai University:Natural Science Edition
基金
国家自然科学基金资助项目(60872114)
上海市重点学科建设资助项目(S30108)
上海市科委重点实验室资助项目(08DZ2231100)
关键词
模糊特征
篡改检测
最小二乘估计
动态阈值
blur characteristic
forgery detection
least-square estimation
dynamical threshold
