Gamma Correction Parameter Estimation Via Histogram Gap Feature
This paper first analyzes the empty-bin distribution characteristics of the his-togram 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 cor-rection 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.Ex-perimental 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.