基于直方图间隙特征的伽马校正参数估计

Gamma Correction Parameter Estimation Via Histogram Gap Feature

本文分析了经过伽马校正图像的直方图间隙分布特征和在此基础上进行伽马逆变换后直方图的零值特征,并应用逆变换后直方图的零值特征对篡改图像进行精确参数估计。具体来说,首先根据原始图像直方图零间隙的特征判断图像是否经过伽马校正,然后比较直方图两端零值的数量大小来判断参数所在区间,最后通过逆变换后直方图零值特征对待估计参数进行精确估计。实验结果表明,所提出的方法不仅在参数估计准确率方面优于现有方法,且在变换前为不同质量因子的JPEG图像上同样具有较好鲁棒性。

This paper first analyzes the empty-bin distribution characteristics of the histogram of the gamma-corrected image and the gap feature of the histogram after the inverse gamma transformation on the gramma-corrected image.Subsequently,this gap feature from the inverse transform histogram is applied to estimate the tampered image parameters.Specifically,we first determine whether the image has undergone gamma correction by comparing the number of zero values at both ends of the histogram.Then we estimate the parameters accurately by the inverse-transformed histogram gap feature.Experimental results show that the proposed method outperforms the existing methods in terms of parameter estimation accuracy and demonstrating robustness on JPEG images with different quality factors before the transformation.