ML estimation of the resampling factor
ML estimation of the resampling factor
复制标题
重采样因子的 ML 估计
DOI：
10.1109/wifs.2012.6412650
复制
发表时间：
2012
期刊：
影响因子：
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通讯作者：
Pedro Comesaña Alfaro
中科院分区：
文献类型：
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作者：
David Vázquez;Pedro Comesaña Alfaro
在这项工作中，按照最大似然准则解决了篡改检测的重采样因子估计问题。通过依靠重采样之后应用的舍入操作，获得量化的重采样信号的似然函数的近似。从基础统计模型中，导出一维信号的最大似然估计和分段线性插值。对所获得的估计器的性能进行了评估，表明它优于最先进的方法。
In this work, the problem of resampling factor estimation for tampering detection is addressed following the maximum likelihood criterion. By relying on the rounding operation applied after resampling, an approximation of the likelihood function of the quantized resampled signal is obtained. From the underlying statistical model, the maximum likelihood estimate is derived for one-dimensional signals and a piecewise linear interpolation. The performance of the obtained estimator is evaluated, showing that it outperforms state-of-the-art methods.