Abstract: There is a part of background noise in digital image which comes from imaging process.The noise characteristics between image forgery area and the other area are different if images with different noise levels are spliced together.This paper proposed a background noise estimation algorithm based on the statistical properties of skewness.We detected the forgery parts by dividing image into some sub-blocks and computing the noise variance of each ones.This algorithm removes the original image details with DCT transform,estimates noise with the statistical properties of skewness,and estimates the standard deviation of noise with condition of the minimum method.This algorithm improves iterative conditional minimum value method using differential method to calculate the minimum value.This algorithm avoids the problem of setting the initial value,and improves the accuracy of the algorithm.The experimental results show that the proposed noise estimation algorithm has high accuracy and effectiveness in detecting forgery part in spliced images.

Key words: Image forensics,Background noise,Skewness,The standard deviation